hivesterix/hivesterix-dist/src/main/resources/conf/hive-site.xml

<?xml version="1.0"?>
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<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

<configuration>

	<configuration>
		<!-- Hivesterix Execution Parameters -->
		<property>
			<name>hive.hyracks.connectorpolicy</name>
			<value>PIPELINING</value>
		</property>

		<property>
			<name>hive.hyracks.parrallelism</name>
			<value>4</value>
		</property>

		<property>
			<name>hive.algebricks.groupby.external</name>
			<value>true</value>
		</property>
		
		<property>
			<name>hive.algebricks.groupby.external.memory</name>
			<value>33554432</value>
		</property>

		<property>
			<name>hive.algebricks.sort.memory</name>
			<value>33554432</value>
		</property>
		
		<property>
            <name>hive.algebricks.framesize</name>
            <value>32768</value>
        </property>

		<!-- Hive Execution Parameters -->
		<property>
			<name>mapred.reduce.tasks</name>
			<value>-1</value>
			<description>The default number of reduce tasks per job. Typically
				set
				to a prime close to the number of available hosts. Ignored when
				mapred.job.tracker is "local". Hadoop set this to 1 by default,
				whereas hive uses -1 as its default value.
				By setting this property
				to -1, Hive will automatically figure out
				what should be the number
				of reducers.
			</description>
		</property>

		<property>
			<name>hive.exec.reducers.bytes.per.reducer</name>
			<value>1000000000</value>
			<description>size per reducer.The default is 1G, i.e if the input
				size is 10G, it will use 10 reducers.
			</description>
		</property>

		<property>
			<name>hive.exec.reducers.max</name>
			<value>999</value>
			<description>max number of reducers will be used. If the one
				specified in the configuration parameter mapred.reduce.tasks is
				negative, hive will use this one as the max number of reducers when
				automatically determine number of reducers.
			</description>
		</property>

		<property>
			<name>hive.cli.print.header</name>
			<value>false</value>
			<description>Whether to print the names of the columns in query
				output.
			</description>
		</property>

		<property>
			<name>hive.cli.print.current.db</name>
			<value>false</value>
			<description>Whether to include the current database in the hive
				prompt.
			</description>
		</property>

		<property>
			<name>hive.cli.prompt</name>
			<value>hive</value>
			<description>Command line prompt configuration value. Other hiveconf
				can be used in
				this configuration value. Variable substitution will
				only be invoked at
				the hive
				cli startup.
			</description>
		</property>

		<property>
			<name>hive.cli.pretty.output.num.cols</name>
			<value>-1</value>
			<description>The number of columns to use when formatting output
				generated
				by the DESCRIBE PRETTY table_name command. If the value of
				this
				property
				is -1, then hive will use the auto-detected terminal
				width.
			</description>
		</property>

		<property>
			<name>hive.exec.scratchdir</name>
			<value>/tmp/hive-${user.name}</value>
			<description>Scratch space for Hive jobs</description>
		</property>

		<property>
			<name>hive.exec.local.scratchdir</name>
			<value>/tmp/${user.name}</value>
			<description>Local scratch space for Hive jobs</description>
		</property>

		<property>
			<name>hive.test.mode</name>
			<value>false</value>
			<description>whether hive is running in test mode. If yes, it turns
				on sampling and prefixes the output tablename
			</description>
		</property>

		<property>
			<name>hive.test.mode.prefix</name>
			<value>test_</value>
			<description>if hive is running in test mode, prefixes the output
				table by this string
			</description>
		</property>

		<!-- If the input table is not bucketed, the denominator of the tablesample 
			is determinied by the parameter below -->
		<!-- For example, the following query: -->
		<!-- INSERT OVERWRITE TABLE dest -->
		<!-- SELECT col1 from src -->
		<!-- would be converted to -->
		<!-- INSERT OVERWRITE TABLE test_dest -->
		<!-- SELECT col1 from src TABLESAMPLE (BUCKET 1 out of 32 on rand(1)) -->
		<property>
			<name>hive.test.mode.samplefreq</name>
			<value>32</value>
			<description>if hive is running in test mode and table is not
				bucketed, sampling frequency
			</description>
		</property>

		<property>
			<name>hive.test.mode.nosamplelist</name>
			<value></value>
			<description>if hive is running in test mode, dont sample the above
				comma seperated list of tables
			</description>
		</property>

		<property>
			<name>hive.metastore.uris</name>
			<value></value>
			<description>Thrift uri for the remote metastore. Used by metastore
				client to connect to remote metastore.
			</description>
		</property>

		<property>
			<name>javax.jdo.option.ConnectionURL</name>
			<value>jdbc:derby:;databaseName=metastore_db;create=true</value>
			<description>JDBC connect string for a JDBC metastore</description>
		</property>

		<property>
			<name>javax.jdo.option.ConnectionDriverName</name>
			<value>org.apache.derby.jdbc.EmbeddedDriver</value>
			<description>Driver class name for a JDBC metastore</description>
		</property>

		<property>
			<name>javax.jdo.PersistenceManagerFactoryClass</name>
			<value>org.datanucleus.jdo.JDOPersistenceManagerFactory</value>
			<description>class implementing the jdo persistence</description>
		</property>

		<property>
			<name>javax.jdo.option.DetachAllOnCommit</name>
			<value>true</value>
			<description>detaches all objects from session so that they can be
				used after transaction is committed
			</description>
		</property>

		<property>
			<name>javax.jdo.option.NonTransactionalRead</name>
			<value>true</value>
			<description>reads outside of transactions</description>
		</property>

		<property>
			<name>javax.jdo.option.ConnectionUserName</name>
			<value>APP</value>
			<description>username to use against metastore database</description>
		</property>

		<property>
			<name>javax.jdo.option.ConnectionPassword</name>
			<value>mine</value>
			<description>password to use against metastore database</description>
		</property>

		<property>
			<name>javax.jdo.option.Multithreaded</name>
			<value>true</value>
			<description>Set this to true if multiple threads access metastore
				through JDO concurrently.
			</description>
		</property>

		<property>
			<name>datanucleus.connectionPoolingType</name>
			<value>DBCP</value>
			<description>Uses a DBCP connection pool for JDBC metastore
			</description>
		</property>

		<property>
			<name>datanucleus.validateTables</name>
			<value>false</value>
			<description>validates existing schema against code. turn this on if
				you want to verify existing schema
			</description>
		</property>

		<property>
			<name>datanucleus.validateColumns</name>
			<value>false</value>
			<description>validates existing schema against code. turn this on if
				you want to verify existing schema
			</description>
		</property>

		<property>
			<name>datanucleus.validateConstraints</name>
			<value>false</value>
			<description>validates existing schema against code. turn this on if
				you want to verify existing schema
			</description>
		</property>

		<property>
			<name>datanucleus.storeManagerType</name>
			<value>rdbms</value>
			<description>metadata store type</description>
		</property>

		<property>
			<name>datanucleus.autoCreateSchema</name>
			<value>true</value>
			<description>creates necessary schema on a startup if one doesn't
				exist. set this to false, after creating it once
			</description>
		</property>

		<property>
			<name>datanucleus.autoStartMechanismMode</name>
			<value>checked</value>
			<description>throw exception if metadata tables are incorrect
			</description>
		</property>

		<property>
			<name>datanucleus.transactionIsolation</name>
			<value>read-committed</value>
			<description>Default transaction isolation level for identity
				generation.
			</description>
		</property>

		<property>
			<name>datanucleus.cache.level2</name>
			<value>false</value>
			<description>Use a level 2 cache. Turn this off if metadata is
				changed independently of hive metastore server
			</description>
		</property>

		<property>
			<name>datanucleus.cache.level2.type</name>
			<value>SOFT</value>
			<description>SOFT=soft reference based cache, WEAK=weak reference
				based cache.
			</description>
		</property>

		<property>
			<name>datanucleus.identifierFactory</name>
			<value>datanucleus</value>
			<description>Name of the identifier factory to use when generating
				table/column names etc. 'datanucleus' is used for backward
				compatibility
			</description>
		</property>

		<property>
			<name>datanucleus.plugin.pluginRegistryBundleCheck</name>
			<value>LOG</value>
			<description>Defines what happens when plugin bundles are found and
				are duplicated [EXCEPTION|LOG|NONE]
			</description>
		</property>

		<property>
			<name>hive.metastore.warehouse.dir</name>
			<value>/user/hive/warehouse</value>
			<description>location of default database for the warehouse
			</description>
		</property>

		<property>
			<name>hive.metastore.execute.setugi</name>
			<value>false</value>
			<description>In unsecure mode, setting this property to true will
				cause the metastore to execute DFS operations using the client's
				reported user and group permissions. Note that this property must be
				set on both the client and server sides. Further note that its best
				effort. If client sets its to true and server sets it to false,
				client setting will be ignored.
			</description>
		</property>

		<property>
			<name>hive.metastore.event.listeners</name>
			<value></value>
			<description>list of comma seperated listeners for metastore events.
			</description>
		</property>

		<property>
			<name>hive.metastore.partition.inherit.table.properties</name>
			<value></value>
			<description>list of comma seperated keys occurring in table
				properties which will get inherited to newly created partitions. *
				implies all the keys will get inherited.
			</description>
		</property>

		<property>
			<name>hive.metadata.export.location</name>
			<value></value>
			<description>When used in conjunction with the
				org.apache.hadoop.hive.ql.parse.MetaDataExportListener pre event
				listener, it is the location to which the metadata will be exported.
				The default is an empty string, which results in the metadata being
				exported to the current user's home directory on HDFS.
			</description>
		</property>

		<property>
			<name>hive.metadata.move.exported.metadata.to.trash</name>
			<value></value>
			<description>When used in conjunction with the
				org.apache.hadoop.hive.ql.parse.MetaDataExportListener pre event
				listener, this setting determines if the metadata that is exported
				will subsequently be moved to the user's trash directory alongside
				the dropped table data. This ensures that the metadata will be
				cleaned up along with the dropped table data.
			</description>
		</property>

		<property>
			<name>hive.metastore.partition.name.whitelist.pattern</name>
			<value></value>
			<description>Partition names will be checked against this regex
				pattern and rejected if not matched.
			</description>
		</property>

		<property>
			<name>hive.metastore.end.function.listeners</name>
			<value></value>
			<description>list of comma separated listeners for the end of
				metastore functions.
			</description>
		</property>

		<property>
			<name>hive.metastore.event.expiry.duration</name>
			<value>0</value>
			<description>Duration after which events expire from events table (in
				seconds)
			</description>
		</property>

		<property>
			<name>hive.metastore.event.clean.freq</name>
			<value>0</value>
			<description>Frequency at which timer task runs to purge expired
				events in metastore(in seconds).
			</description>
		</property>

		<property>
			<name>hive.metastore.connect.retries</name>
			<value>5</value>
			<description>Number of retries while opening a connection to
				metastore
			</description>
		</property>

		<property>
			<name>hive.metastore.failure.retries</name>
			<value>3</value>
			<description>Number of retries upon failure of Thrift metastore calls
			</description>
		</property>

		<property>
			<name>hive.metastore.client.connect.retry.delay</name>
			<value>1</value>
			<description>Number of seconds for the client to wait between
				consecutive connection attempts
			</description>
		</property>

		<property>
			<name>hive.metastore.client.socket.timeout</name>
			<value>20</value>
			<description>MetaStore Client socket timeout in seconds</description>
		</property>

		<property>
			<name>hive.metastore.rawstore.impl</name>
			<value>org.apache.hadoop.hive.metastore.ObjectStore</value>
			<description>Name of the class that implements
				org.apache.hadoop.hive.metastore.rawstore interface. This class is
				used to store and retrieval of raw metadata objects such as table,
				database
			</description>
		</property>

		<property>
			<name>hive.metastore.batch.retrieve.max</name>
			<value>300</value>
			<description>Maximum number of objects (tables/partitions) can be
				retrieved from metastore in one batch. The higher the number, the
				less the number of round trips is needed to the Hive metastore
				server, but it may also cause higher memory requirement at the
				client side.
			</description>
		</property>

		<property>
			<name>hive.metastore.batch.retrieve.table.partition.max</name>
			<value>1000</value>
			<description>Maximum number of table partitions that metastore
				internally retrieves in one batch.
			</description>
		</property>

		<property>
			<name>hive.default.fileformat</name>
			<value>TextFile</value>
			<description>Default file format for CREATE TABLE statement. Options
				are TextFile and SequenceFile. Users can explicitly say CREATE TABLE
				... STORED AS &lt;TEXTFILE|SEQUENCEFILE&gt; to override
			</description>
		</property>

		<property>
			<name>hive.fileformat.check</name>
			<value>true</value>
			<description>Whether to check file format or not when loading data
				files
			</description>
		</property>

		<property>
			<name>hive.map.aggr</name>
			<value>true</value>
			<description>Whether to use map-side aggregation in Hive Group By
				queries
			</description>
		</property>

		<property>
			<name>hive.groupby.skewindata</name>
			<value>false</value>
			<description>Whether there is skew in data to optimize group by
				queries
			</description>
		</property>

		<property>
			<name>hive.optimize.multigroupby.common.distincts</name>
			<value>true</value>
			<description>Whether to optimize a multi-groupby query with the same
				distinct.
				Consider a query like:

				from src
				insert overwrite table dest1
				select col1, count(distinct colx) group by
				col1
				insert overwrite table
				dest2 select col2, count(distinct colx) group by
				col2;

				With this
				parameter set to true, first we spray by the distinct value
				(colx),
				and then
				perform the 2 groups bys. This makes sense if map-side
				aggregation is
				turned off. However,
				with maps-side aggregation, it
				might be useful in some cases to treat
				the 2 inserts independently,
				thereby performing the query above in 2MR jobs instead of 3 (due to
				spraying by distinct key first).
				If this parameter is turned off, we
				dont consider the fact that the
				distinct key is the same across
				different MR jobs.
			</description>
		</property>

		<property>
			<name>hive.groupby.mapaggr.checkinterval</name>
			<value>100000</value>
			<description>Number of rows after which size of the grouping
				keys/aggregation classes is performed
			</description>
		</property>

		<property>
			<name>hive.mapred.local.mem</name>
			<value>0</value>
			<description>For local mode, memory of the mappers/reducers
			</description>
		</property>

		<property>
			<name>hive.mapjoin.followby.map.aggr.hash.percentmemory</name>
			<value>0.3</value>
			<description>Portion of total memory to be used by map-side grup
				aggregation hash table, when this group by is followed by map join
			</description>
		</property>

		<property>
			<name>hive.map.aggr.hash.force.flush.memory.threshold</name>
			<value>0.9</value>
			<description>The max memory to be used by map-side grup aggregation
				hash table, if the memory usage is higher than this number, force to
				flush data
			</description>
		</property>

		<property>
			<name>hive.map.aggr.hash.percentmemory</name>
			<value>0.5</value>
			<description>Portion of total memory to be used by map-side grup
				aggregation hash table
			</description>
		</property>

		<property>
			<name>hive.map.aggr.hash.min.reduction</name>
			<value>0.5</value>
			<description>Hash aggregation will be turned off if the ratio between
				hash
				table size and input rows is bigger than this number. Set to 1
				to make
				sure
				hash aggregation is never turned off.
			</description>
		</property>

		<property>
			<name>hive.optimize.cp</name>
			<value>true</value>
			<description>Whether to enable column pruner</description>
		</property>

		<property>
			<name>hive.optimize.index.filter</name>
			<value>false</value>
			<description>Whether to enable automatic use of indexes</description>
		</property>

		<property>
			<name>hive.optimize.index.groupby</name>
			<value>false</value>
			<description>Whether to enable optimization of group-by queries using
				Aggregate indexes.
			</description>
		</property>

		<property>
			<name>hive.optimize.ppd</name>
			<value>true</value>
			<description>Whether to enable predicate pushdown</description>
		</property>

		<property>
			<name>hive.optimize.ppd.storage</name>
			<value>true</value>
			<description>Whether to push predicates down into storage handlers.
				Ignored when hive.optimize.ppd is false.
			</description>
		</property>

		<property>
			<name>hive.ppd.recognizetransivity</name>
			<value>true</value>
			<description>Whether to transitively replicate predicate filters over
				equijoin conditions.
			</description>
		</property>

		<property>
			<name>hive.optimize.groupby</name>
			<value>true</value>
			<description>Whether to enable the bucketed group by from bucketed
				partitions/tables.
			</description>
		</property>

		<property>
			<name>hive.optimize.skewjoin.compiletime</name>
			<value>false</value>
			<description>Whether to create a separate plan for skewed keys for
				the tables in the join.
				This is based on the skewed keys stored in
				the metadata. At compile
				time, the plan is broken
				into different
				joins: one for the skewed keys, and the other for the
				remaining keys.
				And then,
				a union is performed for the 2 joins generated above. So
				unless the
				same skewed key is present
				in both the joined tables, the
				join for the skewed key will be
				performed as a map-side join.

				The main
				difference between this paramater and hive.optimize.skewjoin
				is that
				this parameter
				uses the skew information stored in the metastore to
				optimize the plan
				at compile time itself.
				If there is no skew
				information in the metadata, this parameter will
				not have any affect.
				Both hive.optimize.skewjoin.compiletime and hive.optimize.skewjoin
				should be set to true.
				Ideally, hive.optimize.skewjoin should be
				renamed as
				hive.optimize.skewjoin.runtime, but not doing
				so for
				backward compatibility.

				If the skew information is correctly stored
				in the metadata,
				hive.optimize.skewjoin.compiletime
				would change the
				query plan to take care of it, and
				hive.optimize.skewjoin will be a
				no-op.
			</description>
		</property>

		<property>
			<name>hive.optimize.union.remove</name>
			<value>false</value>
			<description>
				Whether to remove the union and push the operators
				between union and the
				filesink above
				union. This avoids an extra scan
				of the output by union. This is
				independently useful for union
				queries, and specially useful when
				hive.optimize.skewjoin.compiletime is set
				to true, since an
				extra
				union is inserted.

				The merge is triggered if either of
				hive.merge.mapfiles or
				hive.merge.mapredfiles is set to true.
				If the
				user has set hive.merge.mapfiles to true and
				hive.merge.mapredfiles
				to false, the idea was the
				number of reducers are few, so the number
				of files anyway are small.
				However, with this optimization,
				we are
				increasing the number of files possibly by a big margin. So, we
				merge aggresively.
			</description>
		</property>

		<property>
			<name>hive.mapred.supports.subdirectories</name>
			<value>false</value>
			<description>Whether the version of hadoop which is running supports
				sub-directories for tables/partitions.
				Many hive optimizations can be
				applied if the hadoop version supports
				sub-directories for
				tables/partitions. It was added by MAPREDUCE-1501
			</description>
		</property>

		<property>
			<name>hive.multigroupby.singlemr</name>
			<value>true</value>
			<description>Whether to optimize multi group by query to generate
				single M/R
				job plan. If the multi group by query has common group by
				keys, it will
				be
				optimized to generate single M/R job.
			</description>
		</property>

		<property>
			<name>hive.map.groupby.sorted</name>
			<value>false</value>
			<description>If the bucketing/sorting properties of the table exactly
				match the grouping key, whether to
				perform the group by in the mapper
				by using BucketizedHiveInputFormat. The
				only downside to this
				is that
				it limits the number of mappers to the number of files.
			</description>
		</property>

		<property>
			<name>hive.map.groupby.sorted.testmode</name>
			<value>false</value>
			<description>If the bucketing/sorting properties of the table exactly
				match the grouping key, whether to
				perform the group by in the mapper
				by using BucketizedHiveInputFormat. If
				the test mode is set, the plan
				is not converted, but a query property is set to denote the same.
			</description>
		</property>

		<property>
			<name>hive.new.job.grouping.set.cardinality</name>
			<value>30</value>
			<description>
				Whether a new map-reduce job should be launched for
				grouping
				sets/rollups/cubes.
				For a query like: select a, b, c,
				count(1) from T group by a, b, c with
				rollup;
				4 rows are created per
				row: (a, b, c), (a, b, null), (a, null, null),
				(null, null, null).
				This can lead to explosion across map-reduce boundary if the
				cardinality
				of T is very high,
				and map-side aggregation does not do a
				very good job.

				This parameter decides if hive should add an
				additional map-reduce job.
				If the grouping set
				cardinality (4 in the
				example above), is more than this value, a new MR job is
				added under
				the
				assumption that the orginal group by will reduce the data size.
			</description>
		</property>

		<property>
			<name>hive.join.emit.interval</name>
			<value>1000</value>
			<description>How many rows in the right-most join operand Hive should
				buffer before emitting the join result.
			</description>
		</property>

		<property>
			<name>hive.join.cache.size</name>
			<value>25000</value>
			<description>How many rows in the joining tables (except the
				streaming table) should be cached in memory.
			</description>
		</property>

		<property>
			<name>hive.mapjoin.bucket.cache.size</name>
			<value>100</value>
			<description>How many values in each keys in the map-joined table
				should be cached in memory.
			</description>
		</property>

		<property>
			<name>hive.mapjoin.cache.numrows</name>
			<value>25000</value>
			<description>How many rows should be cached by jdbm for map join.
			</description>
		</property>

		<property>
			<name>hive.optimize.skewjoin</name>
			<value>false</value>
			<description>Whether to enable skew join optimization.
				The algorithm
				is as follows: At runtime, detect the keys with a large
				skew. Instead
				of
				processing those keys, store them temporarily in a hdfs directory.
				In a
				follow-up map-reduce
				job, process those skewed keys. The same key
				need not be skewed for all
				the tables, and so,
				the follow-up
				map-reduce job (for the skewed keys) would be much
				faster, since it
				would be a
				map-join.
			</description>
		</property>

		<property>
			<name>hive.skewjoin.key</name>
			<value>100000</value>
			<description>Determine if we get a skew key in join. If we see more
				than the specified number of rows with the same key in join
				operator,
				we think the key as a skew join key.
			</description>
		</property>

		<property>
			<name>hive.skewjoin.mapjoin.map.tasks</name>
			<value>10000</value>
			<description> Determine the number of map task used in the follow up
				map join job
				for a skew join. It should be used together with
				hive.skewjoin.mapjoin.min.split
				to perform a fine grained control.
			</description>
		</property>

		<property>
			<name>hive.skewjoin.mapjoin.min.split</name>
			<value>33554432</value>
			<description> Determine the number of map task at most used in the
				follow up map join job
				for a skew join by specifying the minimum
				split size. It should be used
				together with
				hive.skewjoin.mapjoin.map.tasks to perform a fine grained control.
			</description>
		</property>

		<property>
			<name>hive.mapred.mode</name>
			<value>nonstrict</value>
			<description>The mode in which the hive operations are being
				performed.
				In strict mode, some risky queries are not allowed to run.
				They
				include:
				Cartesian Product.
				No partition being picked up for a
				query.
				Comparing bigints and strings.
				Comparing bigints and doubles.
				Orderby without limit.
			</description>
		</property>

		<property>
			<name>hive.enforce.bucketmapjoin</name>
			<value>false</value>
			<description>If the user asked for bucketed map-side join, and it
				cannot be performed,
				should the query fail or not ? For eg, if the
				buckets in the tables being
				joined are
				not a multiple of each other,
				bucketed map-side join cannot be
				performed, and the
				query will fail if
				hive.enforce.bucketmapjoin is set to true.
			</description>
		</property>

		<property>
			<name>hive.exec.script.maxerrsize</name>
			<value>100000</value>
			<description>Maximum number of bytes a script is allowed to emit to
				standard error (per map-reduce task). This prevents runaway scripts
				from filling logs partitions to capacity
			</description>
		</property>

		<property>
			<name>hive.exec.script.allow.partial.consumption</name>
			<value>false</value>
			<description> When enabled, this option allows a user script to exit
				successfully without consuming all the data from the standard input.
			</description>
		</property>

		<property>
			<name>hive.script.operator.id.env.var</name>
			<value>HIVE_SCRIPT_OPERATOR_ID</value>
			<description> Name of the environment variable that holds the unique
				script operator ID in the user's transform function (the custom
				mapper/reducer that the user has specified in the query)
			</description>
		</property>

		<property>
			<name>hive.script.operator.truncate.env</name>
			<value>false</value>
			<description>Truncate each environment variable for external script
				in scripts operator to 20KB (to fit system limits)
			</description>
		</property>

		<property>
			<name>hive.exec.compress.output</name>
			<value>false</value>
			<description> This controls whether the final outputs of a query (to
				a local/hdfs file or a hive table) is compressed. The compression
				codec and other options are determined from hadoop config variables
				mapred.output.compress*
			</description>
		</property>

		<property>
			<name>hive.exec.compress.intermediate</name>
			<value>false</value>
			<description> This controls whether intermediate files produced by
				hive between multiple map-reduce jobs are compressed. The
				compression codec and other options are determined from hadoop
				config variables mapred.output.compress*
			</description>
		</property>

		<property>
			<name>hive.exec.parallel</name>
			<value>false</value>
			<description>Whether to execute jobs in parallel</description>
		</property>

		<property>
			<name>hive.exec.parallel.thread.number</name>
			<value>8</value>
			<description>How many jobs at most can be executed in parallel
			</description>
		</property>

		<property>
			<name>hive.exec.rowoffset</name>
			<value>false</value>
			<description>Whether to provide the row offset virtual column
			</description>
		</property>

		<property>
			<name>hive.task.progress</name>
			<value>false</value>
			<description>Whether Hive should periodically update task progress
				counters during execution. Enabling this allows task progress to be
				monitored more closely in the job tracker, but may impose a
				performance penalty. This flag is automatically set to true for jobs
				with hive.exec.dynamic.partition set to true.
			</description>
		</property>

		<property>
			<name>hive.hwi.war.file</name>
			<value>lib/hive-hwi-@VERSION@.war</value>
			<description>This sets the path to the HWI war file, relative to
				${HIVE_HOME}.
			</description>
		</property>

		<property>
			<name>hive.hwi.listen.host</name>
			<value>0.0.0.0</value>
			<description>This is the host address the Hive Web Interface will
				listen on
			</description>
		</property>

		<property>
			<name>hive.hwi.listen.port</name>
			<value>9999</value>
			<description>This is the port the Hive Web Interface will listen on
			</description>
		</property>

		<property>
			<name>hive.exec.pre.hooks</name>
			<value></value>
			<description>Comma-separated list of pre-execution hooks to be
				invoked for each statement. A pre-execution hook is specified as the
				name of a Java class which implements the
				org.apache.hadoop.hive.ql.hooks.ExecuteWithHookContext interface.
			</description>
		</property>

		<property>
			<name>hive.exec.post.hooks</name>
			<value></value>
			<description>Comma-separated list of post-execution hooks to be
				invoked for each statement. A post-execution hook is specified as
				the name of a Java class which implements the
				org.apache.hadoop.hive.ql.hooks.ExecuteWithHookContext interface.
			</description>
		</property>

		<property>
			<name>hive.exec.failure.hooks</name>
			<value></value>
			<description>Comma-separated list of on-failure hooks to be invoked
				for each statement. An on-failure hook is specified as the name of
				Java class which implements the
				org.apache.hadoop.hive.ql.hooks.ExecuteWithHookContext interface.
			</description>
		</property>

		<property>
			<name>hive.metastore.init.hooks</name>
			<value></value>
			<description>A comma separated list of hooks to be invoked at the
				beginning of HMSHandler initialization. Aninit hook is specified as
				the name of Java class which extends
				org.apache.hadoop.hive.metastore.MetaStoreInitListener.
			</description>
		</property>

		<property>
			<name>hive.client.stats.publishers</name>
			<value></value>
			<description>Comma-separated list of statistics publishers to be
				invoked on counters on each job. A client stats publisher is
				specified as the name of a Java class which implements the
				org.apache.hadoop.hive.ql.stats.ClientStatsPublisher interface.
			</description>
		</property>

		<property>
			<name>hive.client.stats.counters</name>
			<value></value>
			<description>Subset of counters that should be of interest for
				hive.client.stats.publishers (when one wants to limit their
				publishing). Non-display names should be used
			</description>
		</property>

		<property>
			<name>hive.merge.mapfiles</name>
			<value>true</value>
			<description>Merge small files at the end of a map-only job
			</description>
		</property>

		<property>
			<name>hive.merge.mapredfiles</name>
			<value>false</value>
			<description>Merge small files at the end of a map-reduce job
			</description>
		</property>

		<property>
			<name>hive.heartbeat.interval</name>
			<value>1000</value>
			<description>Send a heartbeat after this interval - used by mapjoin
				and filter operators
			</description>
		</property>

		<property>
			<name>hive.merge.size.per.task</name>
			<value>256000000</value>
			<description>Size of merged files at the end of the job</description>
		</property>

		<property>
			<name>hive.merge.smallfiles.avgsize</name>
			<value>16000000</value>
			<description>When the average output file size of a job is less than
				this number, Hive will start an additional map-reduce job to merge
				the output files into bigger files. This is only done for map-only
				jobs if hive.merge.mapfiles is true, and for map-reduce jobs if
				hive.merge.mapredfiles is true.
			</description>
		</property>

		<property>
			<name>hive.mapjoin.smalltable.filesize</name>
			<value>25000000</value>
			<description>The threshold for the input file size of the small
				tables; if the file size is smaller than this threshold, it will try
				to convert the common join into map join
			</description>
		</property>

		<property>
			<name>hive.ignore.mapjoin.hint</name>
			<value>true</value>
			<description>Ignore the mapjoin hint</description>
		</property>

		<property>
			<name>hive.mapjoin.localtask.max.memory.usage</name>
			<value>0.90</value>
			<description>This number means how much memory the local task can
				take to hold the key/value into in-memory hash table; If the local
				task's memory usage is more than this number, the local task will be
				abort by themself. It means the data of small table is too large to
				be hold in the memory.
			</description>
		</property>

		<property>
			<name>hive.mapjoin.followby.gby.localtask.max.memory.usage</name>
			<value>0.55</value>
			<description>This number means how much memory the local task can
				take to hold the key/value into in-memory hash table when this map
				join followed by a group by; If the local task's memory usage is
				more than this number, the local task will be abort by themself. It
				means the data of small table is too large to be hold in the memory.
			</description>
		</property>

		<property>
			<name>hive.mapjoin.check.memory.rows</name>
			<value>100000</value>
			<description>The number means after how many rows processed it needs
				to check the memory usage
			</description>
		</property>

		<property>
			<name>hive.auto.convert.join</name>
			<value>false</value>
			<description>Whether Hive enable the optimization about converting
				common join into mapjoin based on the input file size
			</description>
		</property>

		<property>
			<name>hive.auto.convert.join.noconditionaltask</name>
			<value>true</value>
			<description>Whether Hive enable the optimization about converting
				common join into mapjoin based on the input file
				size. If this
				paramater is on, and the sum of size for n-1 of the
				tables/partitions for a n-way join is smaller than the
				specified
				size, the join is directly converted to a mapjoin (there is no
				conditional task).
			</description>
		</property>

		<property>
			<name>hive.auto.convert.join.noconditionaltask.size</name>
			<value>10000000</value>
			<description>If hive.auto.convert.join.noconditionaltask is off, this
				parameter does not take affect. However, if it
				is on, and the sum of
				size for n-1 of the tables/partitions for a
				n-way join is smaller
				than this size, the join is directly
				converted to a mapjoin(there is
				no conditional task). The default is 10MB
			</description>
		</property>

		<property>
			<name>hive.optimize.mapjoin.mapreduce</name>
			<value>false</value>
			<description>If hive.auto.convert.join is off, this parameter does
				not take
				affect. If it is on, and if there are map-join jobs followed
				by a
				map-reduce
				job (for e.g a group by), each map-only job is merged
				with the
				following
				map-reduce job.
			</description>
		</property>

		<property>
			<name>hive.script.auto.progress</name>
			<value>false</value>
			<description>Whether Hive Tranform/Map/Reduce Clause should
				automatically send progress information to TaskTracker to avoid the
				task getting killed because of inactivity. Hive sends progress
				information when the script is outputting to stderr. This option
				removes the need of periodically producing stderr messages, but
				users should be cautious because this may prevent infinite loops in
				the scripts to be killed by TaskTracker.
			</description>
		</property>

		<property>
			<name>hive.script.serde</name>
			<value>org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe</value>
			<description>The default serde for trasmitting input data to and
				reading output data from the user scripts.
			</description>
		</property>

		<property>
			<name>hive.binary.record.max.length</name>
			<value>1000</value>
			<description>Read from a binary stream and treat each
				hive.binary.record.max.length bytes as a record.
				The last record
				before the end of stream can have less than
				hive.binary.record.max.length bytes
			</description>
		</property>


		<property>
			<name>hive.script.recordreader</name>
			<value>org.apache.hadoop.hive.ql.exec.TextRecordReader</value>
			<description>The default record reader for reading data from the user
				scripts.
			</description>
		</property>

		<property>
			<name>hive.script.recordwriter</name>
			<value>org.apache.hadoop.hive.ql.exec.TextRecordWriter</value>
			<description>The default record writer for writing data to the user
				scripts.
			</description>
		</property>

		<property>
			<name>hive.input.format</name>
			<value>org.apache.hadoop.hive.ql.io.CombineHiveInputFormat</value>
			<description>The default input format. Set this to HiveInputFormat if
				you encounter problems with CombineHiveInputFormat.
			</description>
		</property>

		<property>
			<name>hive.udtf.auto.progress</name>
			<value>false</value>
			<description>Whether Hive should automatically send progress
				information to TaskTracker when using UDTF's to prevent the task
				getting killed because of inactivity. Users should be cautious
				because this may prevent TaskTracker from killing tasks with infinte
				loops.
			</description>
		</property>

		<property>
			<name>hive.mapred.reduce.tasks.speculative.execution</name>
			<value>true</value>
			<description>Whether speculative execution for reducers should be
				turned on.
			</description>
		</property>

		<property>
			<name>hive.exec.counters.pull.interval</name>
			<value>1000</value>
			<description>The interval with which to poll the JobTracker for the
				counters the running job. The smaller it is the more load there will
				be on the jobtracker, the higher it is the less granular the caught
				will be.
			</description>
		</property>

		<property>
			<name>hive.querylog.location</name>
			<value>/tmp/${user.name}</value>
			<description>
				Location of Hive run time structured log file
			</description>
		</property>

		<property>
			<name>hive.querylog.enable.plan.progress</name>
			<value>true</value>
			<description>
				Whether to log the plan's progress every time a job's
				progress is checked.
				These logs are written to the location specified
				by
				hive.querylog.location
			</description>
		</property>

		<property>
			<name>hive.querylog.plan.progress.interval</name>
			<value>60000</value>
			<description>
				The interval to wait between logging the plan's progress
				in
				milliseconds.
				If there is a whole number percentage change in the
				progress of the
				mappers or the reducers,
				the progress is logged
				regardless of this value.
				The actual interval will be the ceiling of
				(this value divided by the
				value of
				hive.exec.counters.pull.interval)
				multiplied by the value of hive.exec.counters.pull.interval
				I.e. if
				it is not divide evenly by the value of
				hive.exec.counters.pull.interval it will be
				logged less frequently
				than specified.
				This only has an effect if
				hive.querylog.enable.plan.progress is set to
				true.
			</description>
		</property>

		<property>
			<name>hive.enforce.bucketing</name>
			<value>false</value>
			<description>Whether bucketing is enforced. If true, while inserting
				into the table, bucketing is enforced.
			</description>
		</property>

		<property>
			<name>hive.enforce.sorting</name>
			<value>false</value>
			<description>Whether sorting is enforced. If true, while inserting
				into the table, sorting is enforced.
			</description>
		</property>

		<property>
			<name>hive.optimize.bucketingsorting</name>
			<value>true</value>
			<description>If hive.enforce.bucketing or hive.enforce.sorting is
				true, dont create a reducer for enforcing
				bucketing/sorting for
				queries of the form:
				insert overwrite table T2 select * from T1;
				where T1 and T2 are bucketed/sorted by the same keys into the same
				number
				of buckets.
			</description>
		</property>

		<property>
			<name>hive.enforce.sortmergebucketmapjoin</name>
			<value>false</value>
			<description>If the user asked for sort-merge bucketed map-side join,
				and it cannot be performed,
				should the query fail or not ?
			</description>
		</property>

		<property>
			<name>hive.auto.convert.sortmerge.join</name>
			<value>false</value>
			<description>Will the join be automatically converted to a sort-merge
				join, if the joined tables pass
				the criteria for sort-merge join.
			</description>
		</property>

		<property>
			<name>hive.auto.convert.sortmerge.join.bigtable.selection.policy
			</name>
			<value>org.apache.hadoop.hive.ql.optimizer.AvgPartitionSizeBasedBigTableSelectorForAutoSMJ
			</value>
			<description>The policy to choose the big table for automatic
				conversion to sort-merge join.
				By default, the table with the largest
				partitions is assigned the big
				table. All policies are:
				. based on
				position of the table - the leftmost table is selected
				org.apache.hadoop.hive.ql.optimizer.LeftmostBigTableSMJ.
				. based on
				total size (all the partitions selected in the query) of
				the table
				org.apache.hadoop.hive.ql.optimizer.TableSizeBasedBigTableSelectorForAutoSMJ.
				. based on average size (all the partitions selected in the query)
				of the table
				org.apache.hadoop.hive.ql.optimizer.AvgPartitionSizeBasedBigTableSelectorForAutoSMJ.
				New policies can be added in future.
			</description>
		</property>

		<property>
			<name>hive.metastore.ds.connection.url.hook</name>
			<value></value>
			<description>Name of the hook to use for retriving the JDO connection
				URL. If empty, the value in javax.jdo.option.ConnectionURL is used
			</description>
		</property>

		<property>
			<name>hive.metastore.ds.retry.attempts</name>
			<value>1</value>
			<description>The number of times to retry a metastore call if there
				were a connection error
			</description>
		</property>

		<property>
			<name>hive.metastore.ds.retry.interval</name>
			<value>1000</value>
			<description>The number of miliseconds between metastore retry
				attempts
			</description>
		</property>

		<property>
			<name>hive.metastore.server.min.threads</name>
			<value>200</value>
			<description>Minimum number of worker threads in the Thrift server's
				pool.
			</description>
		</property>

		<property>
			<name>hive.metastore.server.max.threads</name>
			<value>100000</value>
			<description>Maximum number of worker threads in the Thrift server's
				pool.
			</description>
		</property>

		<property>
			<name>hive.metastore.server.tcp.keepalive</name>
			<value>true</value>
			<description>Whether to enable TCP keepalive for the metastore
				server. Keepalive will prevent accumulation of half-open
				connections.
			</description>
		</property>

		<property>
			<name>hive.metastore.sasl.enabled</name>
			<value>false</value>
			<description>If true, the metastore thrift interface will be secured
				with SASL. Clients must authenticate with Kerberos.
			</description>
		</property>

		<property>
			<name>hive.metastore.thrift.framed.transport.enabled</name>
			<value>false</value>
			<description>If true, the metastore thrift interface will use
				TFramedTransport. When false (default) a standard TTransport is
				used.
			</description>
		</property>

		<property>
			<name>hive.metastore.kerberos.keytab.file</name>
			<value></value>
			<description>The path to the Kerberos Keytab file containing the
				metastore thrift server's service principal.
			</description>
		</property>

		<property>
			<name>hive.metastore.kerberos.principal</name>
			<value>hive-metastore/_HOST@EXAMPLE.COM</value>
			<description>The service principal for the metastore thrift server.
				The special string _HOST will be replaced automatically with the
				correct host name.
			</description>
		</property>

		<property>
			<name>hive.cluster.delegation.token.store.class</name>
			<value>org.apache.hadoop.hive.thrift.MemoryTokenStore</value>
			<description>The delegation token store implementation. Set to
				org.apache.hadoop.hive.thrift.ZooKeeperTokenStore for load-balanced
				cluster.
			</description>
		</property>

		<property>
			<name>hive.cluster.delegation.token.store.zookeeper.connectString
			</name>
			<value>localhost:2181</value>
			<description>The ZooKeeper token store connect string.</description>
		</property>

		<property>
			<name>hive.cluster.delegation.token.store.zookeeper.znode</name>
			<value>/hive/cluster/delegation</value>
			<description>The root path for token store data.</description>
		</property>

		<property>
			<name>hive.cluster.delegation.token.store.zookeeper.acl</name>
			<value>sasl:hive/host1@EXAMPLE.COM:cdrwa,sasl:hive/host2@EXAMPLE.COM:cdrwa
			</value>
			<description>ACL for token store entries. List comma separated all
				server principals for the cluster.
			</description>
		</property>

		<property>
			<name>hive.metastore.cache.pinobjtypes</name>
			<value>Table,StorageDescriptor,SerDeInfo,Partition,Database,Type,FieldSchema,Order
			</value>
			<description>List of comma separated metastore object types that
				should be pinned in the cache
			</description>
		</property>

		<property>
			<name>hive.optimize.reducededuplication</name>
			<value>true</value>
			<description>Remove extra map-reduce jobs if the data is already
				clustered by the same key which needs to be used again. This should
				always be set to true. Since it is a new feature, it has been made
				configurable.
			</description>
		</property>

		<property>
			<name>hive.optimize.reducededuplication.min.reducer</name>
			<value>4</value>
			<description>Reduce deduplication merges two RSs by moving
				key/parts/reducer-num of the child RS to parent RS.
				That means if
				reducer-num of the child RS is fixed (order by or forced
				bucketing)
				and small, it can make very slow, single MR.
				The optimization will be
				disabled if number of reducers is less than
				specified value.
			</description>
		</property>

		<property>
			<name>hive.exec.dynamic.partition</name>
			<value>true</value>
			<description>Whether or not to allow dynamic partitions in DML/DDL.
			</description>
		</property>

		<property>
			<name>hive.exec.dynamic.partition.mode</name>
			<value>strict</value>
			<description>In strict mode, the user must specify at least one
				static partition in case the user accidentally overwrites all
				partitions.
			</description>
		</property>

		<property>
			<name>hive.exec.max.dynamic.partitions</name>
			<value>1000</value>
			<description>Maximum number of dynamic partitions allowed to be
				created in total.
			</description>
		</property>

		<property>
			<name>hive.exec.max.dynamic.partitions.pernode</name>
			<value>100</value>
			<description>Maximum number of dynamic partitions allowed to be
				created in each mapper/reducer node.
			</description>
		</property>

		<property>
			<name>hive.exec.max.created.files</name>
			<value>100000</value>
			<description>Maximum number of HDFS files created by all
				mappers/reducers in a MapReduce job.
			</description>
		</property>

		<property>
			<name>hive.exec.default.partition.name</name>
			<value>__HIVE_DEFAULT_PARTITION__</value>
			<description>The default partition name in case the dynamic partition
				column value is null/empty string or anyother values that cannot be
				escaped. This value must not contain any special character used in
				HDFS URI (e.g., ':', '%', '/' etc). The user has to be aware that
				the dynamic partition value should not contain this value to avoid
				confusions.
			</description>
		</property>

		<property>
			<name>hive.stats.dbclass</name>
			<value>jdbc:derby</value>
			<description>The default database that stores temporary hive
				statistics.
			</description>
		</property>

		<property>
			<name>hive.stats.autogather</name>
			<value>true</value>
			<description>A flag to gather statistics automatically during the
				INSERT OVERWRITE command.
			</description>
		</property>

		<property>
			<name>hive.stats.jdbcdriver</name>
			<value>org.apache.derby.jdbc.EmbeddedDriver</value>
			<description>The JDBC driver for the database that stores temporary
				hive statistics.
			</description>
		</property>

		<property>
			<name>hive.stats.dbconnectionstring</name>
			<value>jdbc:derby:;databaseName=TempStatsStore;create=true</value>
			<description>The default connection string for the database that
				stores temporary hive statistics.
			</description>
		</property>

		<property>
			<name>hive.stats.default.publisher</name>
			<value></value>
			<description>The Java class (implementing the StatsPublisher
				interface) that is used by default if hive.stats.dbclass is not JDBC
				or HBase.
			</description>
		</property>

		<property>
			<name>hive.stats.default.aggregator</name>
			<value></value>
			<description>The Java class (implementing the StatsAggregator
				interface) that is used by default if hive.stats.dbclass is not JDBC
				or HBase.
			</description>
		</property>

		<property>
			<name>hive.stats.jdbc.timeout</name>
			<value>30</value>
			<description>Timeout value (number of seconds) used by JDBC
				connection and statements.
			</description>
		</property>

		<property>
			<name>hive.stats.retries.max</name>
			<value>0</value>
			<description>Maximum number of retries when stats
				publisher/aggregator got an exception updating intermediate
				database. Default is no tries on failures.
			</description>
		</property>

		<property>
			<name>hive.stats.retries.wait</name>
			<value>3000</value>
			<description>The base waiting window (in milliseconds) before the
				next retry. The actual wait time is calculated by baseWindow *
				failues baseWindow * (failure 1) * (random number between
				[0.0,1.0]).
			</description>
		</property>

		<property>
			<name>hive.stats.reliable</name>
			<value>false</value>
			<description>Whether queries will fail because stats cannot be
				collected completely accurately.
				If this is set to true,
				reading/writing from/into a partition may fail
				becuase the stats
				could not be computed accurately.
			</description>
		</property>

		<property>
			<name>hive.stats.collect.tablekeys</name>
			<value>false</value>
			<description>Whether join and group by keys on tables are derived and
				maintained in the QueryPlan.
				This is useful to identify how tables
				are accessed and to determine if
				they should be bucketed.
			</description>
		</property>

		<property>
			<name>hive.stats.collect.scancols</name>
			<value>false</value>
			<description>Whether column accesses are tracked in the QueryPlan.
				This is useful to identify how tables are accessed and to determine
				if there are wasted columns that can be trimmed.
			</description>
		</property>

		<property>
			<name>hive.stats.ndv.error</name>
			<value>20.0</value>
			<description>Standard error expressed in percentage. Provides a
				tradeoff between accuracy and compute cost.A lower value for error
				indicates higher accuracy and a higher compute cost.
			</description>
		</property>

		<property>
			<name>hive.stats.key.prefix.max.length</name>
			<value>200</value>
			<description>
				Determines if when the prefix of the key used for
				intermediate stats
				collection
				exceeds a certain length, a hash of the
				key is used instead. If the value
				&lt; 0 then hashing
				is never used,
				if the value >= 0 then hashing is used only when the
				key prefixes
				length
				exceeds that value. The key prefix is defined as everything
				preceding the
				task ID in the key.
			</description>
		</property>

		<property>
			<name>hive.support.concurrency</name>
			<value>false</value>
			<description>Whether hive supports concurrency or not. A zookeeper
				instance must be up and running for the default hive lock manager to
				support read-write locks.
			</description>
		</property>

		<property>
			<name>hive.lock.numretries</name>
			<value>100</value>
			<description>The number of times you want to try to get all the locks
			</description>
		</property>

		<property>
			<name>hive.unlock.numretries</name>
			<value>10</value>
			<description>The number of times you want to retry to do one unlock
			</description>
		</property>

		<property>
			<name>hive.lock.sleep.between.retries</name>
			<value>60</value>
			<description>The sleep time (in seconds) between various retries
			</description>
		</property>

		<property>
			<name>hive.zookeeper.quorum</name>
			<value></value>
			<description>The list of zookeeper servers to talk to. This is only
				needed for read/write locks.
			</description>
		</property>

		<property>
			<name>hive.zookeeper.client.port</name>
			<value>2181</value>
			<description>The port of zookeeper servers to talk to. This is only
				needed for read/write locks.
			</description>
		</property>

		<property>
			<name>hive.zookeeper.session.timeout</name>
			<value>600000</value>
			<description>Zookeeper client's session timeout. The client is
				disconnected, and as a result, all locks released, if a heartbeat is
				not sent in the timeout.
			</description>
		</property>

		<property>
			<name>hive.zookeeper.namespace</name>
			<value>hive_zookeeper_namespace</value>
			<description>The parent node under which all zookeeper nodes are
				created.
			</description>
		</property>

		<property>
			<name>hive.zookeeper.clean.extra.nodes</name>
			<value>false</value>
			<description>Clean extra nodes at the end of the session.
			</description>
		</property>

		<property>
			<name>fs.har.impl</name>
			<value>org.apache.hadoop.hive.shims.HiveHarFileSystem</value>
			<description>The implementation for accessing Hadoop Archives. Note
				that this won't be applicable to Hadoop vers less than 0.20
			</description>
		</property>

		<property>
			<name>hive.archive.enabled</name>
			<value>false</value>
			<description>Whether archiving operations are permitted</description>
		</property>

		<property>
			<name>hive.fetch.output.serde</name>
			<value>org.apache.hadoop.hive.serde2.DelimitedJSONSerDe</value>
			<description>The serde used by FetchTask to serialize the fetch
				output.
			</description>
		</property>

		<property>
			<name>hive.exec.mode.local.auto</name>
			<value>false</value>
			<description> Let hive determine whether to run in local mode
				automatically
			</description>
		</property>

		<property>
			<name>hive.exec.drop.ignorenonexistent</name>
			<value>true</value>
			<description>
				Do not report an error if DROP TABLE/VIEW specifies a
				non-existent
				table/view
			</description>
		</property>

		<property>
			<name>hive.exec.show.job.failure.debug.info</name>
			<value>true</value>
			<description>
				If a job fails, whether to provide a link in the CLI to
				the task with
				the
				most failures, along with debugging hints if
				applicable.
			</description>
		</property>

		<property>
			<name>hive.auto.progress.timeout</name>
			<value>0</value>
			<description>
				How long to run autoprogressor for the script/UDTF
				operators (in
				seconds).
				Set to 0 for forever.
			</description>
		</property>

		<!-- HBase Storage Handler Parameters -->

		<property>
			<name>hive.hbase.wal.enabled</name>
			<value>true</value>
			<description>Whether writes to HBase should be forced to the
				write-ahead log. Disabling this improves HBase write performance at
				the risk of lost writes in case of a crash.
			</description>
		</property>

		<property>
			<name>hive.table.parameters.default</name>
			<value></value>
			<description>Default property values for newly created tables
			</description>
		</property>

		<property>
			<name>hive.entity.separator</name>
			<value>@</value>
			<description>Separator used to construct names of tables and
				partitions. For example, dbname@tablename@partitionname
			</description>
		</property>

		<property>
			<name>hive.ddl.createtablelike.properties.whitelist</name>
			<value></value>
			<description>Table Properties to copy over when executing a Create
				Table Like.
			</description>
		</property>

		<property>
			<name>hive.variable.substitute</name>
			<value>true</value>
			<description>This enables substitution using syntax like ${var}
				${system:var} and ${env:var}.
			</description>
		</property>

		<property>
			<name>hive.variable.substitute.depth</name>
			<value>40</value>
			<description>The maximum replacements the substitution engine will
				do.
			</description>
		</property>

		<property>
			<name>hive.conf.validation</name>
			<value>true</value>
			<description>Eables type checking for registered hive configurations
			</description>
		</property>

		<property>
			<name>hive.security.authorization.enabled</name>
			<value>false</value>
			<description>enable or disable the hive client authorization
			</description>
		</property>

		<property>
			<name>hive.security.authorization.createtable.user.grants</name>
			<value></value>
			<description>the privileges automatically granted to some users
				whenever a table gets created.
				An example like
				"userX,userY:select;userZ:create" will grant select
				privilege to
				userX and userY,
				and grant create privilege to userZ whenever a new
				table created.
			</description>
		</property>

		<property>
			<name>hive.security.authorization.createtable.group.grants</name>
			<value></value>
			<description>the privileges automatically granted to some groups
				whenever a table gets created.
				An example like
				"groupX,groupY:select;groupZ:create" will grant select
				privilege to
				groupX and groupY,
				and grant create privilege to groupZ whenever a
				new table created.
			</description>
		</property>

		<property>
			<name>hive.security.authorization.createtable.role.grants</name>
			<value></value>
			<description>the privileges automatically granted to some roles
				whenever a table gets created.
				An example like
				"roleX,roleY:select;roleZ:create" will grant select
				privilege to
				roleX and roleY,
				and grant create privilege to roleZ whenever a new
				table created.
			</description>
		</property>

		<property>
			<name>hive.security.authorization.createtable.owner.grants</name>
			<value></value>
			<description>the privileges automatically granted to the owner
				whenever a table gets created.
				An example like "select,drop" will
				grant select and drop privilege to
				the owner of the table
			</description>
		</property>

		<property>
			<name>hive.metastore.authorization.storage.checks</name>
			<value>false</value>
			<description>Should the metastore do authorization checks against the
				underlying storage
				for operations like drop-partition (disallow the
				drop-partition if the
				user in
				question doesn't have permissions to
				delete the corresponding directory
				on the storage).
			</description>
		</property>

		<property>
			<name>hive.error.on.empty.partition</name>
			<value>false</value>
			<description>Whether to throw an excpetion if dynamic partition
				insert generates empty results.
			</description>
		</property>

		<property>
			<name>hive.index.compact.file.ignore.hdfs</name>
			<value>false</value>
			<description>True the hdfs location stored in the index file will be
				igbored at runtime.
				If the data got moved or the name of the cluster
				got changed, the
				index data should still be usable.
			</description>
		</property>

		<property>
			<name>hive.optimize.index.filter.compact.minsize</name>
			<value>5368709120</value>
			<description>Minimum size (in bytes) of the inputs on which a compact
				index is automatically used.
			</description>
		</property>

		<property>
			<name>hive.optimize.index.filter.compact.maxsize</name>
			<value>-1</value>
			<description>Maximum size (in bytes) of the inputs on which a compact
				index is automatically used.
				A negative number is equivalent to
				infinity.
			</description>
		</property>

		<property>
			<name>hive.index.compact.query.max.size</name>
			<value>10737418240</value>
			<description>The maximum number of bytes that a query using the
				compact index can read. Negative value is equivalent to infinity.
			</description>
		</property>

		<property>
			<name>hive.index.compact.query.max.entries</name>
			<value>10000000</value>
			<description>The maximum number of index entries to read during a
				query that uses the compact index. Negative value is equivalent to
				infinity.
			</description>
		</property>

		<property>
			<name>hive.index.compact.binary.search</name>
			<value>true</value>
			<description>Whether or not to use a binary search to find the
				entries in an index table that match the filter, where possible
			</description>
		</property>

		<property>
			<name>hive.exim.uri.scheme.whitelist</name>
			<value>hdfs,pfile</value>
			<description>A comma separated list of acceptable URI schemes for
				import and export.
			</description>
		</property>

		<property>
			<name>hive.lock.mapred.only.operation</name>
			<value>false</value>
			<description>This param is to control whether or not only do lock on
				queries
				that need to execute at least one mapred job.
			</description>
		</property>

		<property>
			<name>hive.limit.row.max.size</name>
			<value>100000</value>
			<description>When trying a smaller subset of data for simple LIMIT,
				how much size we need to guarantee
				each row to have at least.
			</description>
		</property>

		<property>
			<name>hive.limit.optimize.limit.file</name>
			<value>10</value>
			<description>When trying a smaller subset of data for simple LIMIT,
				maximum number of files we can
				sample.
			</description>
		</property>

		<property>
			<name>hive.limit.optimize.enable</name>
			<value>false</value>
			<description>Whether to enable to optimization to trying a smaller
				subset of data for simple LIMIT first.
			</description>
		</property>

		<property>
			<name>hive.limit.optimize.fetch.max</name>
			<value>50000</value>
			<description>Maximum number of rows allowed for a smaller subset of
				data for simple LIMIT, if it is a fetch query.
				Insert queries are not
				restricted by this limit.
			</description>
		</property>

		<property>
			<name>hive.rework.mapredwork</name>
			<value>false</value>
			<description>should rework the mapred work or not.
				This is first
				introduced by SymlinkTextInputFormat to replace symlink
				files with
				real paths at compile time.
			</description>
		</property>

		<property>
			<name>hive.exec.concatenate.check.index</name>
			<value>true</value>
			<description>If this sets to true, hive will throw error when doing
				'alter table tbl_name [partSpec] concatenate' on a table/partition
				that has indexes on it. The reason the user want to set this to true
				is because it can help user to avoid handling all index drop,
				recreation,
				rebuild work. This is very helpful for tables with
				thousands of partitions.
			</description>
		</property>

		<property>
			<name>hive.sample.seednumber</name>
			<value>0</value>
			<description>A number used to percentage sampling. By changing this
				number, user will change the subsets
				of data sampled.
			</description>
		</property>

		<property>
			<name>hive.io.exception.handlers</name>
			<value></value>
			<description>A list of io exception handler class names. This is used
				to construct a list exception handlers to handle exceptions thrown
				by record readers
			</description>
		</property>

		<property>
			<name>hive.autogen.columnalias.prefix.label</name>
			<value>_c</value>
			<description>String used as a prefix when auto generating column
				alias.
				By default the prefix label will be appended with a column
				position
				number to form the column alias. Auto generation would
				happen if an
				aggregate function is used in a select clause without an
				explicit
				alias.
			</description>
		</property>

		<property>
			<name>hive.autogen.columnalias.prefix.includefuncname</name>
			<value>false</value>
			<description>Whether to include function name in the column alias
				auto generated by hive.
			</description>
		</property>

		<property>
			<name>hive.exec.perf.logger</name>
			<value>org.apache.hadoop.hive.ql.log.PerfLogger</value>
			<description>The class responsible logging client side performance
				metrics. Must be a subclass of
				org.apache.hadoop.hive.ql.log.PerfLogger
			</description>
		</property>

		<property>
			<name>hive.start.cleanup.scratchdir</name>
			<value>false</value>
			<description>To cleanup the hive scratchdir while starting the hive
				server
			</description>
		</property>

		<property>
			<name>hive.output.file.extension</name>
			<value></value>
			<description>String used as a file extension for output files. If not
				set, defaults to the codec extension for text files (e.g. ".gz"), or
				no extension otherwise.
			</description>
		</property>

		<property>
			<name>hive.insert.into.multilevel.dirs</name>
			<value>false</value>
			<description>Where to insert into multilevel directories like
				"insert
				directory '/HIVEFT25686/chinna/' from table"
			</description>
		</property>

		<property>
			<name>hive.warehouse.subdir.inherit.perms</name>
			<value>false</value>
			<description>Set this to true if the the table directories should
				inherit the
				permission of the warehouse or database directory instead
				of being created
				with the permissions derived from dfs umask
			</description>
		</property>

		<property>
			<name>hive.exec.job.debug.capture.stacktraces</name>
			<value>true</value>
			<description>Whether or not stack traces parsed from the task logs of
				a sampled failed task for
				each failed job should be stored in the
				SessionState
			</description>
		</property>

		<property>
			<name>hive.exec.driver.run.hooks</name>
			<value></value>
			<description>A comma separated list of hooks which implement
				HiveDriverRunHook and will be run at the
				beginning and end of
				Driver.run, these will be run in the order specified
			</description>
		</property>

		<property>
			<name>hive.ddl.output.format</name>
			<value>text</value>
			<description>
				The data format to use for DDL output. One of "text"
				(for human
				readable text) or "json" (for a json object).
			</description>
		</property>

		<property>
			<name>hive.transform.escape.input</name>
			<value>false</value>
			<description>
				This adds an option to escape special chars (newlines,
				carriage returns
				and
				tabs) when they are passed to the user script.
				This is useful if the hive
				tables
				can contain data that contains
				special characters.
			</description>
		</property>

		<property>
			<name>hive.exec.rcfile.use.explicit.header</name>
			<value>true</value>
			<description>
				If this is set the header for RC Files will simply be
				RCF. If this is
				not
				set the header will be that borrowed from sequence
				files, e.g. SEQ-
				followed
				by the input and output RC File formats.
			</description>
		</property>

		<property>
			<name>hive.multi.insert.move.tasks.share.dependencies</name>
			<value>false</value>
			<description>
				If this is set all move tasks for tables/partitions (not
				directories)
				at the end of a
				multi-insert query will only begin once
				the dependencies for all these move
				tasks have been
				met.
				Advantages: If
				concurrency is enabled, the locks will only be released once the
				query has
				finished, so with this config enabled, the time when the
				table/partition is
				generated will be much closer to when the lock on
				it is released.
				Disadvantages: If concurrency is not enabled, with
				this disabled,
				the tables/partitions which
				are produced by this query
				and finish earlier will be available for
				querying
				much earlier. Since
				the locks are only released once the query finishes,
				this
				does not
				apply if concurrency is enabled.
			</description>
		</property>

		<property>
			<name>hive.fetch.task.conversion</name>
			<value>minimal</value>
			<description>
				Some select queries can be converted to single FETCH
				task minimizing
				latency.
				Currently the query should be single sourced
				not having any subquery and
				should not have
				any aggregations or
				distincts (which incurrs RS), lateral views and
				joins.
				1. minimal :
				SELECT STAR, FILTER on partition columns, LIMIT only
				2. more :
				SELECT, FILTER, LIMIT only (TABLESAMPLE, virtual columns)
			</description>
		</property>

		<property>
			<name>hive.hmshandler.retry.attempts</name>
			<value>1</value>
			<description>The number of times to retry a HMSHandler call if there
				were a connection error
			</description>
		</property>

		<property>
			<name>hive.hmshandler.retry.interval</name>
			<value>1000</value>
			<description>The number of miliseconds between HMSHandler retry
				attempts
			</description>
		</property>

		<property>
			<name>hive.server.read.socket.timeout</name>
			<value>10</value>
			<description>Timeout for the HiveServer to close the connection if no
				response from the client in N seconds, defaults to 10 seconds.
			</description>
		</property>

		<property>
			<name>hive.server.tcp.keepalive</name>
			<value>true</value>
			<description>Whether to enable TCP keepalive for the Hive server.
				Keepalive will prevent accumulation of half-open connections.
			</description>
		</property>

		<property>
			<name>hive.decode.partition.name</name>
			<value>false</value>
			<description>Whether to show the unquoted partition names in query
				results.
			</description>
		</property>

		<property>
			<name>hive.log4j.file</name>
			<value></value>
			<description>Hive log4j configuration file.
				If the property is not
				set, then logging will be initialized using
				hive-log4j.properties
				found on the classpath.
				If the property is set, the value must be a
				valid URI (java.net.URI,
				e.g. "file:///tmp/my-logging.properties"),
				which you can then
				extract a URL from and pass to
				PropertyConfigurator.configure(URL).
			</description>
		</property>

		<property>
			<name>hive.exec.log4j.file</name>
			<value></value>
			<description>Hive log4j configuration file for execution mode(sub
				command).
				If the property is not set, then logging will be
				initialized using
				hive-exec-log4j.properties found on the classpath.
				If the property is set, the value must be a valid URI (java.net.URI,
				e.g. "file:///tmp/my-logging.properties"), which you can then
				extract a URL from and pass to PropertyConfigurator.configure(URL).
			</description>
		</property>

		<property>
			<name>hive.exec.infer.bucket.sort</name>
			<value>false</value>
			<description>
				If this is set, when writing partitions, the metadata
				will include the
				bucketing/sorting
				properties with which the data was
				written if any (this will not overwrite the
				metadata
				inherited from
				the table if the table is bucketed/sorted)
			</description>
		</property>

		<property>
			<name>hive.exec.infer.bucket.sort.num.buckets.power.two</name>
			<value>false</value>
			<description>
				If this is set, when setting the number of reducers for
				the map reduce
				task which writes the
				final output files, it will
				choose a number which is a power of two,
				unless the user specifies
				the number of reducers to use using mapred.reduce.tasks. The number
				of
				reducers
				may be set to a power of two, only to be followed by a
				merge task
				meaning preventing
				anything from being inferred.
				With
				hive.exec.infer.bucket.sort set to true:
				Advantages: If this is not
				set, the number of buckets for partitions will seem
				arbitrary,
				which
				means that the number of mappers used for optimized joins, for
				example, will
				be very low. With this set, since the number of buckets
				used for any
				partition is
				a power of two, the number of mappers used
				for optimized joins will
				be the least
				number of buckets used by any
				partition being joined.
				Disadvantages: This may mean a much larger or
				much smaller number of reducers
				being used in the
				final map reduce
				job, e.g. if a job was originally going to take 257
				reducers,
				it will
				now take 512 reducers, similarly if the max number of reducers
				is
				511,
				and a job was going to use this many, it will now use 256
				reducers.

			</description>
		</property>

		<property>
			<name>hive.groupby.orderby.position.alias</name>
			<value>false</value>
			<description>Whether to enable using Column Position Alias in Group
				By or Order By
			</description>
		</property>

		<property>
			<name>hive.server2.thrift.min.worker.threads</name>
			<value>5</value>
			<description>Minimum number of Thrift worker threads</description>
		</property>

		<property>
			<name>hive.server2.thrift.max.worker.threads</name>
			<value>100</value>
			<description>Maximum number of Thrift worker threads</description>
		</property>

		<property>
			<name>hive.server2.thrift.port</name>
			<value>10000</value>
			<description>Port number of HiveServer2 Thrift interface.
				Can be
				overridden by setting $HIVE_SERVER2_THRIFT_PORT
			</description>
		</property>

		<property>
			<name>hive.server2.thrift.bind.host</name>
			<value>localhost</value>
			<description>Bind host on which to run the HiveServer2 Thrift
				interface.
				Can be overridden by setting
				$HIVE_SERVER2_THRIFT_BIND_HOST
			</description>
		</property>

		<property>
			<name>hive.server2.authentication</name>
			<value>NONE</value>
			<description>
				Client authentication types.
				NONE: no authentication
				check
				LDAP: LDAP/AD based authentication
				KERBEROS: Kerberos/GSSAPI
				authentication
				CUSTOM: Custom authentication provider
				(Use with
				property hive.server2.custom.authentication.class)
			</description>
		</property>

		<property>
			<name>hive.server2.custom.authentication.class</name>
			<value></value>
			<description>
				Custom authentication class. Used when property
				'hive.server2.authentication' is set to 'CUSTOM'. Provided class
				must be a proper implementation of the interface
				org.apache.hive.service.auth.PasswdAuthenticationProvider.
				HiveServer2
				will call its Authenticate(user, passed) method to
				authenticate
				requests.
				The implementation may optionally extend the
				Hadoop's
				org.apache.hadoop.conf.Configured class to grab Hive's
				Configuration
				object.
			</description>
		</property>

		<property>
			<name>>hive.server2.authentication.kerberos.principal</name>
			<value></value>
			<description>
				Kerberos server principal
			</description>
		</property>

		<property>
			<name>>hive.server2.authentication.kerberos.keytab</name>
			<value></value>
			<description>
				Kerberos keytab file for server principal
			</description>
		</property>

		<property>
			<name>hive.server2.authentication.ldap.url</name>
			<value></value>
			<description>
				LDAP connection URL
			</description>
		</property>

		<property>
			<name>hive.server2.authentication.ldap.baseDN</name>
			<value></value>
			<description>
				LDAP base DN
			</description>
		</property>

		<property>
			<name>hive.server2.enable.doAs</name>
			<value>true</value>
			<description>
				Setting this property to true will have hive server2
				execute
				hive operations as the user making the calls to it.
			</description>
		</property>


	</configuration>

	<!-- Hive Execution Parameters -->
	<property>
		<name>mapred.reduce.tasks</name>
		<value>-1</value>
		<description>The default number of reduce tasks per job. Typically set
			to a prime close to the number of available hosts. Ignored when
			mapred.job.tracker is "local". Hadoop set this to 1 by default,
			whereas hive uses -1 as its default value.
			By setting this property to
			-1, Hive will automatically figure out what
			should be the number of
			reducers.
		</description>
	</property>

	<property>
		<name>hive.exec.reducers.bytes.per.reducer</name>
		<value>1000000000</value>
		<description>size per reducer.The default is 1G, i.e if the input size
			is 10G, it will use 10 reducers.
		</description>
	</property>

	<property>
		<name>hive.exec.reducers.max</name>
		<value>999</value>
		<description>max number of reducers will be used. If the one
			specified
			in the configuration parameter mapred.reduce.tasks is
			negative, hive
			will use this one as the max number of reducers when
			automatically
			determine number of reducers.
		</description>
	</property>

	<property>
		<name>hive.cli.print.header</name>
		<value>false</value>
		<description>Whether to print the names of the columns in query
			output.
		</description>
	</property>

	<property>
		<name>hive.cli.print.current.db</name>
		<value>false</value>
		<description>Whether to include the current database in the hive
			prompt.
		</description>
	</property>

	<property>
		<name>hive.cli.prompt</name>
		<value>hive</value>
		<description>Command line prompt configuration value. Other hiveconf
			can be used in
			this configuration value. Variable substitution will
			only be invoked at
			the hive
			cli startup.
		</description>
	</property>

	<property>
		<name>hive.cli.pretty.output.num.cols</name>
		<value>-1</value>
		<description>The number of columns to use when formatting output
			generated
			by the DESCRIBE PRETTY table_name command. If the value of
			this
			property
			is -1, then hive will use the auto-detected terminal
			width.
		</description>
	</property>

	<property>
		<name>hive.exec.scratchdir</name>
		<value>/tmp/hive-${user.name}</value>
		<description>Scratch space for Hive jobs</description>
	</property>

	<property>
		<name>hive.exec.local.scratchdir</name>
		<value>/tmp/${user.name}</value>
		<description>Local scratch space for Hive jobs</description>
	</property>

	<property>
		<name>hive.test.mode</name>
		<value>false</value>
		<description>whether hive is running in test mode. If yes, it turns on
			sampling and prefixes the output tablename
		</description>
	</property>

	<property>
		<name>hive.test.mode.prefix</name>
		<value>test_</value>
		<description>if hive is running in test mode, prefixes the output
			table by this string
		</description>
	</property>

	<!-- If the input table is not bucketed, the denominator of the tablesample 
		is determinied by the parameter below -->
	<!-- For example, the following query: -->
	<!-- INSERT OVERWRITE TABLE dest -->
	<!-- SELECT col1 from src -->
	<!-- would be converted to -->
	<!-- INSERT OVERWRITE TABLE test_dest -->
	<!-- SELECT col1 from src TABLESAMPLE (BUCKET 1 out of 32 on rand(1)) -->
	<property>
		<name>hive.test.mode.samplefreq</name>
		<value>32</value>
		<description>if hive is running in test mode and table is not
			bucketed, sampling frequency
		</description>
	</property>

	<property>
		<name>hive.test.mode.nosamplelist</name>
		<value></value>
		<description>if hive is running in test mode, dont sample the above
			comma seperated list of tables
		</description>
	</property>

	<property>
		<name>hive.metastore.uris</name>
		<value></value>
		<description>Thrift uri for the remote metastore. Used by metastore
			client to connect to remote metastore.
		</description>
	</property>

	<property>
		<name>javax.jdo.option.ConnectionURL</name>
		<value>jdbc:derby:;databaseName=metastore_db;create=true</value>
		<description>JDBC connect string for a JDBC metastore</description>
	</property>

	<property>
		<name>javax.jdo.option.ConnectionDriverName</name>
		<value>org.apache.derby.jdbc.EmbeddedDriver</value>
		<description>Driver class name for a JDBC metastore</description>
	</property>

	<property>
		<name>javax.jdo.PersistenceManagerFactoryClass</name>
		<value>org.datanucleus.jdo.JDOPersistenceManagerFactory</value>
		<description>class implementing the jdo persistence</description>
	</property>

	<property>
		<name>javax.jdo.option.DetachAllOnCommit</name>
		<value>true</value>
		<description>detaches all objects from session so that they can be
			used after transaction is committed
		</description>
	</property>

	<property>
		<name>javax.jdo.option.NonTransactionalRead</name>
		<value>true</value>
		<description>reads outside of transactions</description>
	</property>

	<property>
		<name>javax.jdo.option.ConnectionUserName</name>
		<value>APP</value>
		<description>username to use against metastore database</description>
	</property>

	<property>
		<name>javax.jdo.option.ConnectionPassword</name>
		<value>mine</value>
		<description>password to use against metastore database</description>
	</property>

	<property>
		<name>javax.jdo.option.Multithreaded</name>
		<value>true</value>
		<description>Set this to true if multiple threads access metastore
			through JDO concurrently.
		</description>
	</property>

	<property>
		<name>datanucleus.connectionPoolingType</name>
		<value>DBCP</value>
		<description>Uses a DBCP connection pool for JDBC metastore
		</description>
	</property>

	<property>
		<name>datanucleus.validateTables</name>
		<value>false</value>
		<description>validates existing schema against code. turn this on if
			you want to verify existing schema
		</description>
	</property>

	<property>
		<name>datanucleus.validateColumns</name>
		<value>false</value>
		<description>validates existing schema against code. turn this on if
			you want to verify existing schema
		</description>
	</property>

	<property>
		<name>datanucleus.validateConstraints</name>
		<value>false</value>
		<description>validates existing schema against code. turn this on if
			you want to verify existing schema
		</description>
	</property>

	<property>
		<name>datanucleus.storeManagerType</name>
		<value>rdbms</value>
		<description>metadata store type</description>
	</property>

	<property>
		<name>datanucleus.autoCreateSchema</name>
		<value>true</value>
		<description>creates necessary schema on a startup if one doesn't
			exist. set this to false, after creating it once
		</description>
	</property>

	<property>
		<name>datanucleus.autoStartMechanismMode</name>
		<value>checked</value>
		<description>throw exception if metadata tables are incorrect
		</description>
	</property>

	<property>
		<name>datanucleus.transactionIsolation</name>
		<value>read-committed</value>
		<description>Default transaction isolation level for identity
			generation.
		</description>
	</property>

	<property>
		<name>datanucleus.cache.level2</name>
		<value>false</value>
		<description>Use a level 2 cache. Turn this off if metadata is changed
			independently of hive metastore server
		</description>
	</property>

	<property>
		<name>datanucleus.cache.level2.type</name>
		<value>SOFT</value>
		<description>SOFT=soft reference based cache, WEAK=weak reference
			based cache.
		</description>
	</property>

	<property>
		<name>datanucleus.identifierFactory</name>
		<value>datanucleus</value>
		<description>Name of the identifier factory to use when generating
			table/column names etc. 'datanucleus' is used for backward
			compatibility
		</description>
	</property>

	<property>
		<name>datanucleus.plugin.pluginRegistryBundleCheck</name>
		<value>LOG</value>
		<description>Defines what happens when plugin bundles are found and
			are duplicated [EXCEPTION|LOG|NONE]
		</description>
	</property>

	<property>
		<name>hive.metastore.warehouse.dir</name>
		<value>/user/hive/warehouse</value>
		<description>location of default database for the warehouse
		</description>
	</property>

	<property>
		<name>hive.metastore.execute.setugi</name>
		<value>false</value>
		<description>In unsecure mode, setting this property to true will
			cause the metastore to execute DFS operations using the client's
			reported user and group permissions. Note that this property must be
			set on both the client and server sides. Further note that its best
			effort. If client sets its to true and server sets it to false,
			client setting will be ignored.
		</description>
	</property>

	<property>
		<name>hive.metastore.event.listeners</name>
		<value></value>
		<description>list of comma seperated listeners for metastore events.
		</description>
	</property>

	<property>
		<name>hive.metastore.partition.inherit.table.properties</name>
		<value></value>
		<description>list of comma seperated keys occurring in table
			properties which will get inherited to newly created partitions. *
			implies all the keys will get inherited.
		</description>
	</property>

	<property>
		<name>hive.metadata.export.location</name>
		<value></value>
		<description>When used in conjunction with the
			org.apache.hadoop.hive.ql.parse.MetaDataExportListener pre event
			listener, it is the location to which the metadata will be exported.
			The default is an empty string, which results in the metadata being
			exported to the current user's home directory on HDFS.
		</description>
	</property>

	<property>
		<name>hive.metadata.move.exported.metadata.to.trash</name>
		<value></value>
		<description>When used in conjunction with the
			org.apache.hadoop.hive.ql.parse.MetaDataExportListener pre event
			listener, this setting determines if the metadata that is exported
			will subsequently be moved to the user's trash directory alongside
			the dropped table data. This ensures that the metadata will be
			cleaned up along with the dropped table data.
		</description>
	</property>

	<property>
		<name>hive.metastore.partition.name.whitelist.pattern</name>
		<value></value>
		<description>Partition names will be checked against this regex
			pattern and rejected if not matched.
		</description>
	</property>

	<property>
		<name>hive.metastore.end.function.listeners</name>
		<value></value>
		<description>list of comma separated listeners for the end of
			metastore functions.
		</description>
	</property>

	<property>
		<name>hive.metastore.event.expiry.duration</name>
		<value>0</value>
		<description>Duration after which events expire from events table (in
			seconds)
		</description>
	</property>

	<property>
		<name>hive.metastore.event.clean.freq</name>
		<value>0</value>
		<description>Frequency at which timer task runs to purge expired
			events in metastore(in seconds).
		</description>
	</property>

	<property>
		<name>hive.metastore.connect.retries</name>
		<value>5</value>
		<description>Number of retries while opening a connection to metastore
		</description>
	</property>

	<property>
		<name>hive.metastore.failure.retries</name>
		<value>3</value>
		<description>Number of retries upon failure of Thrift metastore calls
		</description>
	</property>

	<property>
		<name>hive.metastore.client.connect.retry.delay</name>
		<value>1</value>
		<description>Number of seconds for the client to wait between
			consecutive connection attempts
		</description>
	</property>

	<property>
		<name>hive.metastore.client.socket.timeout</name>
		<value>20</value>
		<description>MetaStore Client socket timeout in seconds</description>
	</property>

	<property>
		<name>hive.metastore.rawstore.impl</name>
		<value>org.apache.hadoop.hive.metastore.ObjectStore</value>
		<description>Name of the class that implements
			org.apache.hadoop.hive.metastore.rawstore interface. This class is
			used to store and retrieval of raw metadata objects such as table,
			database
		</description>
	</property>

	<property>
		<name>hive.metastore.batch.retrieve.max</name>
		<value>300</value>
		<description>Maximum number of objects (tables/partitions) can be
			retrieved from metastore in one batch. The higher the number, the
			less the number of round trips is needed to the Hive metastore
			server, but it may also cause higher memory requirement at the client
			side.
		</description>
	</property>

	<property>
		<name>hive.metastore.batch.retrieve.table.partition.max</name>
		<value>1000</value>
		<description>Maximum number of table partitions that metastore
			internally retrieves in one batch.
		</description>
	</property>

	<property>
		<name>hive.default.fileformat</name>
		<value>TextFile</value>
		<description>Default file format for CREATE TABLE statement. Options
			are TextFile and SequenceFile. Users can explicitly say CREATE TABLE
			... STORED AS &lt;TEXTFILE|SEQUENCEFILE&gt; to override</description>
	</property>

	<property>
		<name>hive.fileformat.check</name>
		<value>true</value>
		<description>Whether to check file format or not when loading data
			files
		</description>
	</property>

	<property>
		<name>hive.map.aggr</name>
		<value>true</value>
		<description>Whether to use map-side aggregation in Hive Group By
			queries
		</description>
	</property>

	<property>
		<name>hive.groupby.skewindata</name>
		<value>false</value>
		<description>Whether there is skew in data to optimize group by
			queries
		</description>
	</property>

	<property>
		<name>hive.optimize.multigroupby.common.distincts</name>
		<value>true</value>
		<description>Whether to optimize a multi-groupby query with the same
			distinct.
			Consider a query like:

			from src
			insert overwrite table dest1
			select col1, count(distinct colx) group by
			col1
			insert overwrite table
			dest2 select col2, count(distinct colx) group by
			col2;

			With this
			parameter set to true, first we spray by the distinct value
			(colx),
			and then
			perform the 2 groups bys. This makes sense if map-side
			aggregation is turned
			off. However,
			with maps-side aggregation, it
			might be useful in some cases to treat the
			2 inserts independently,
			thereby performing the query above in 2MR jobs instead of 3 (due to
			spraying
			by distinct key first).
			If this parameter is turned off, we
			dont consider the fact that the
			distinct key is the same across
			different MR jobs.
		</description>
	</property>

	<property>
		<name>hive.groupby.mapaggr.checkinterval</name>
		<value>100000</value>
		<description>Number of rows after which size of the grouping
			keys/aggregation classes is performed
		</description>
	</property>

	<property>
		<name>hive.mapred.local.mem</name>
		<value>0</value>
		<description>For local mode, memory of the mappers/reducers
		</description>
	</property>

	<property>
		<name>hive.mapjoin.followby.map.aggr.hash.percentmemory</name>
		<value>0.3</value>
		<description>Portion of total memory to be used by map-side grup
			aggregation hash table, when this group by is followed by map join
		</description>
	</property>

	<property>
		<name>hive.map.aggr.hash.force.flush.memory.threshold</name>
		<value>0.9</value>
		<description>The max memory to be used by map-side grup aggregation
			hash table, if the memory usage is higher than this number, force to
			flush data
		</description>
	</property>

	<property>
		<name>hive.map.aggr.hash.percentmemory</name>
		<value>0.5</value>
		<description>Portion of total memory to be used by map-side grup
			aggregation hash table
		</description>
	</property>

	<property>
		<name>hive.map.aggr.hash.min.reduction</name>
		<value>0.5</value>
		<description>Hash aggregation will be turned off if the ratio between
			hash
			table size and input rows is bigger than this number. Set to 1 to
			make
			sure
			hash aggregation is never turned off.
		</description>
	</property>

	<property>
		<name>hive.optimize.cp</name>
		<value>true</value>
		<description>Whether to enable column pruner</description>
	</property>

	<property>
		<name>hive.optimize.index.filter</name>
		<value>false</value>
		<description>Whether to enable automatic use of indexes</description>
	</property>

	<property>
		<name>hive.optimize.index.groupby</name>
		<value>false</value>
		<description>Whether to enable optimization of group-by queries using
			Aggregate indexes.
		</description>
	</property>

	<property>
		<name>hive.optimize.ppd</name>
		<value>true</value>
		<description>Whether to enable predicate pushdown</description>
	</property>

	<property>
		<name>hive.optimize.ppd.storage</name>
		<value>true</value>
		<description>Whether to push predicates down into storage handlers.
			Ignored when hive.optimize.ppd is false.
		</description>
	</property>

	<property>
		<name>hive.ppd.recognizetransivity</name>
		<value>true</value>
		<description>Whether to transitively replicate predicate filters over
			equijoin conditions.
		</description>
	</property>

	<property>
		<name>hive.optimize.groupby</name>
		<value>true</value>
		<description>Whether to enable the bucketed group by from bucketed
			partitions/tables.
		</description>
	</property>

	<property>
		<name>hive.optimize.skewjoin.compiletime</name>
		<value>false</value>
		<description>Whether to create a separate plan for skewed keys for the
			tables in the join.
			This is based on the skewed keys stored in the
			metadata. At compile time,
			the plan is broken
			into different joins: one
			for the skewed keys, and the other for the
			remaining keys. And then,
			a
			union is performed for the 2 joins generated above. So unless the
			same skewed key is present
			in both the joined tables, the join for the
			skewed key will be
			performed as a map-side join.

			The main difference
			between this paramater and hive.optimize.skewjoin is
			that this
			parameter
			uses the skew information stored in the metastore to
			optimize the plan at
			compile time itself.
			If there is no skew
			information in the metadata, this parameter will
			not have any affect.
			Both hive.optimize.skewjoin.compiletime and hive.optimize.skewjoin
			should
			be set to true.
			Ideally, hive.optimize.skewjoin should be
			renamed as
			hive.optimize.skewjoin.runtime, but not doing
			so for
			backward compatibility.

			If the skew information is correctly stored in
			the metadata,
			hive.optimize.skewjoin.compiletime
			would change the query
			plan to take care of it, and hive.optimize.skewjoin
			will be a no-op.
		</description>
	</property>

	<property>
		<name>hive.optimize.union.remove</name>
		<value>false</value>
		<description>
			Whether to remove the union and push the operators
			between union and the
			filesink above
			union. This avoids an extra scan
			of the output by union. This is
			independently useful for union
			queries, and specially useful when hive.optimize.skewjoin.compiletime
			is set
			to true, since an
			extra union is inserted.

			The merge is triggered
			if either of hive.merge.mapfiles or
			hive.merge.mapredfiles is set to
			true.
			If the user has set hive.merge.mapfiles to true and
			hive.merge.mapredfiles to false, the idea was the
			number of reducers
			are few, so the number of files anyway are small.
			However, with this
			optimization,
			we are increasing the number of files possibly by a big
			margin. So, we
			merge aggresively.
		</description>
	</property>

	<property>
		<name>hive.mapred.supports.subdirectories</name>
		<value>false</value>
		<description>Whether the version of hadoop which is running supports
			sub-directories for tables/partitions.
			Many hive optimizations can be
			applied if the hadoop version supports
			sub-directories for
			tables/partitions. It was added by MAPREDUCE-1501
		</description>
	</property>

	<property>
		<name>hive.multigroupby.singlemr</name>
		<value>false</value>
		<description>Whether to optimize multi group by query to generate
			single M/R
			job plan. If the multi group by query has common group by
			keys, it will
			be
			optimized to generate single M/R job.
		</description>
	</property>

	<property>
		<name>hive.map.groupby.sorted</name>
		<value>false</value>
		<description>If the bucketing/sorting properties of the table exactly
			match the grouping key, whether to
			perform the group by in the mapper
			by using BucketizedHiveInputFormat. The
			only downside to this
			is that
			it limits the number of mappers to the number of files.
		</description>
	</property>

	<property>
		<name>hive.map.groupby.sorted.testmode</name>
		<value>false</value>
		<description>If the bucketing/sorting properties of the table exactly
			match the grouping key, whether to
			perform the group by in the mapper
			by using BucketizedHiveInputFormat. If
			the test mode is set, the plan
			is not converted, but a query property is set to denote the same.
		</description>
	</property>

	<property>
		<name>hive.new.job.grouping.set.cardinality</name>
		<value>30</value>
		<description>
			Whether a new map-reduce job should be launched for
			grouping
			sets/rollups/cubes.
			For a query like: select a, b, c, count(1)
			from T group by a, b, c with
			rollup;
			4 rows are created per row: (a, b,
			c), (a, b, null), (a, null, null),
			(null, null, null).
			This can lead to
			explosion across map-reduce boundary if the cardinality
			of T is very
			high,
			and map-side aggregation does not do a very good job.

			This
			parameter decides if hive should add an additional map-reduce job.
			If
			the grouping set
			cardinality (4 in the example above), is more than
			this value, a new MR job is
			added under the
			assumption that the orginal
			group by will reduce the data size.
		</description>
	</property>

	<property>
		<name>hive.join.emit.interval</name>
		<value>1000</value>
		<description>How many rows in the right-most join operand Hive should
			buffer before emitting the join result.
		</description>
	</property>

	<property>
		<name>hive.join.cache.size</name>
		<value>25000</value>
		<description>How many rows in the joining tables (except the streaming
			table) should be cached in memory.
		</description>
	</property>

	<property>
		<name>hive.mapjoin.bucket.cache.size</name>
		<value>100</value>
		<description>How many values in each keys in the map-joined table
			should be cached in memory.
		</description>
	</property>

	<property>
		<name>hive.mapjoin.cache.numrows</name>
		<value>25000</value>
		<description>How many rows should be cached by jdbm for map join.
		</description>
	</property>

	<property>
		<name>hive.optimize.skewjoin</name>
		<value>false</value>
		<description>Whether to enable skew join optimization.
			The algorithm is
			as follows: At runtime, detect the keys with a large
			skew. Instead of
			processing those keys, store them temporarily in a hdfs directory. In
			a
			follow-up map-reduce
			job, process those skewed keys. The same key
			need not be skewed for all
			the tables, and so,
			the follow-up map-reduce
			job (for the skewed keys) would be much faster,
			since it would be a
			map-join.
		</description>
	</property>

	<property>
		<name>hive.skewjoin.key</name>
		<value>100000</value>
		<description>Determine if we get a skew key in join. If we see more
			than the specified number of rows with the same key in join operator,
			we think the key as a skew join key.
		</description>
	</property>

	<property>
		<name>hive.skewjoin.mapjoin.map.tasks</name>
		<value>10000</value>
		<description> Determine the number of map task used in the follow up
			map join job
			for a skew join. It should be used together with
			hive.skewjoin.mapjoin.min.split
			to perform a fine grained control.
		</description>
	</property>

	<property>
		<name>hive.skewjoin.mapjoin.min.split</name>
		<value>33554432</value>
		<description> Determine the number of map task at most used in the
			follow up map join job
			for a skew join by specifying the minimum split
			size. It should be used
			together with
			hive.skewjoin.mapjoin.map.tasks
			to perform a fine grained control.
		</description>
	</property>

	<property>
		<name>hive.mapred.mode</name>
		<value>nonstrict</value>
		<description>The mode in which the hive operations are being
			performed.
			In strict mode, some risky queries are not allowed to run.
			They
			include:
			Cartesian Product.
			No partition being picked up for a
			query.
			Comparing bigints and strings.
			Comparing bigints and doubles.
			Orderby without limit.
		</description>
	</property>

	<property>
		<name>hive.enforce.bucketmapjoin</name>
		<value>false</value>
		<description>If the user asked for bucketed map-side join, and it
			cannot be performed,
			should the query fail or not ? For eg, if the
			buckets in the tables being
			joined are
			not a multiple of each other,
			bucketed map-side join cannot be
			performed, and the
			query will fail if
			hive.enforce.bucketmapjoin is set to true.
		</description>
	</property>

	<property>
		<name>hive.exec.script.maxerrsize</name>
		<value>100000</value>
		<description>Maximum number of bytes a script is allowed to emit to
			standard error (per map-reduce task). This prevents runaway scripts
			from filling logs partitions to capacity
		</description>
	</property>

	<property>
		<name>hive.exec.script.allow.partial.consumption</name>
		<value>false</value>
		<description> When enabled, this option allows a user script to exit
			successfully without consuming all the data from the standard input.
		</description>
	</property>

	<property>
		<name>hive.script.operator.id.env.var</name>
		<value>HIVE_SCRIPT_OPERATOR_ID</value>
		<description> Name of the environment variable that holds the unique
			script operator ID in the user's transform function (the custom
			mapper/reducer that the user has specified in the query)
		</description>
	</property>

	<property>
		<name>hive.script.operator.truncate.env</name>
		<value>false</value>
		<description>Truncate each environment variable for external script in
			scripts operator to 20KB (to fit system limits)
		</description>
	</property>

	<property>
		<name>hive.exec.compress.output</name>
		<value>false</value>
		<description> This controls whether the final outputs of a query (to a
			local/hdfs file or a hive table) is compressed. The compression codec
			and other options are determined from hadoop config variables
			mapred.output.compress*
		</description>
	</property>

	<property>
		<name>hive.exec.compress.intermediate</name>
		<value>false</value>
		<description> This controls whether intermediate files produced by
			hive between multiple map-reduce jobs are compressed. The compression
			codec and other options are determined from hadoop config variables
			mapred.output.compress*
		</description>
	</property>

	<property>
		<name>hive.exec.parallel</name>
		<value>false</value>
		<description>Whether to execute jobs in parallel</description>
	</property>

	<property>
		<name>hive.exec.parallel.thread.number</name>
		<value>8</value>
		<description>How many jobs at most can be executed in parallel
		</description>
	</property>

	<property>
		<name>hive.exec.rowoffset</name>
		<value>false</value>
		<description>Whether to provide the row offset virtual column
		</description>
	</property>

	<property>
		<name>hive.task.progress</name>
		<value>false</value>
		<description>Whether Hive should periodically update task progress
			counters during execution. Enabling this allows task progress to be
			monitored more closely in the job tracker, but may impose a
			performance penalty. This flag is automatically set to true for jobs
			with hive.exec.dynamic.partition set to true.
		</description>
	</property>

	<property>
		<name>hive.hwi.war.file</name>
		<value>lib/hive-hwi-@VERSION@.war</value>
		<description>This sets the path to the HWI war file, relative to
			${HIVE_HOME}.
		</description>
	</property>

	<property>
		<name>hive.hwi.listen.host</name>
		<value>0.0.0.0</value>
		<description>This is the host address the Hive Web Interface will
			listen on
		</description>
	</property>

	<property>
		<name>hive.hwi.listen.port</name>
		<value>9999</value>
		<description>This is the port the Hive Web Interface will listen on
		</description>
	</property>

	<property>
		<name>hive.exec.pre.hooks</name>
		<value></value>
		<description>Comma-separated list of pre-execution hooks to be invoked
			for each statement. A pre-execution hook is specified as the name of
			a Java class which implements the
			org.apache.hadoop.hive.ql.hooks.ExecuteWithHookContext interface.
		</description>
	</property>

	<property>
		<name>hive.exec.post.hooks</name>
		<value></value>
		<description>Comma-separated list of post-execution hooks to be
			invoked for each statement. A post-execution hook is specified as the
			name of a Java class which implements the
			org.apache.hadoop.hive.ql.hooks.ExecuteWithHookContext interface.
		</description>
	</property>

	<property>
		<name>hive.exec.failure.hooks</name>
		<value></value>
		<description>Comma-separated list of on-failure hooks to be invoked
			for each statement. An on-failure hook is specified as the name of
			Java class which implements the
			org.apache.hadoop.hive.ql.hooks.ExecuteWithHookContext interface.
		</description>
	</property>

	<property>
		<name>hive.metastore.init.hooks</name>
		<value></value>
		<description>A comma separated list of hooks to be invoked at the
			beginning of HMSHandler initialization. Aninit hook is specified as
			the name of Java class which extends
			org.apache.hadoop.hive.metastore.MetaStoreInitListener.
		</description>
	</property>

	<property>
		<name>hive.client.stats.publishers</name>
		<value></value>
		<description>Comma-separated list of statistics publishers to be
			invoked on counters on each job. A client stats publisher is
			specified as the name of a Java class which implements the
			org.apache.hadoop.hive.ql.stats.ClientStatsPublisher interface.
		</description>
	</property>

	<property>
		<name>hive.client.stats.counters</name>
		<value></value>
		<description>Subset of counters that should be of interest for
			hive.client.stats.publishers (when one wants to limit their
			publishing). Non-display names should be used
		</description>
	</property>

	<property>
		<name>hive.merge.mapfiles</name>
		<value>true</value>
		<description>Merge small files at the end of a map-only job
		</description>
	</property>

	<property>
		<name>hive.merge.mapredfiles</name>
		<value>false</value>
		<description>Merge small files at the end of a map-reduce job
		</description>
	</property>

	<property>
		<name>hive.heartbeat.interval</name>
		<value>1000</value>
		<description>Send a heartbeat after this interval - used by mapjoin
			and filter operators
		</description>
	</property>

	<property>
		<name>hive.merge.size.per.task</name>
		<value>256000000</value>
		<description>Size of merged files at the end of the job</description>
	</property>

	<property>
		<name>hive.merge.smallfiles.avgsize</name>
		<value>16000000</value>
		<description>When the average output file size of a job is less than
			this number, Hive will start an additional map-reduce job to merge
			the output files into bigger files. This is only done for map-only
			jobs if hive.merge.mapfiles is true, and for map-reduce jobs if
			hive.merge.mapredfiles is true.
		</description>
	</property>

	<property>
		<name>hive.mapjoin.smalltable.filesize</name>
		<value>25000000</value>
		<description>The threshold for the input file size of the small
			tables; if the file size is smaller than this threshold, it will try
			to convert the common join into map join
		</description>
	</property>

	<property>
		<name>hive.ignore.mapjoin.hint</name>
		<value>true</value>
		<description>Ignore the mapjoin hint</description>
	</property>

	<property>
		<name>hive.mapjoin.localtask.max.memory.usage</name>
		<value>0.90</value>
		<description>This number means how much memory the local task can take
			to hold the key/value into in-memory hash table; If the local task's
			memory usage is more than this number, the local task will be abort
			by themself. It means the data of small table is too large to be hold
			in the memory.
		</description>
	</property>

	<property>
		<name>hive.mapjoin.followby.gby.localtask.max.memory.usage</name>
		<value>0.55</value>
		<description>This number means how much memory the local task can take
			to hold the key/value into in-memory hash table when this map join
			followed by a group by; If the local task's memory usage is more than
			this number, the local task will be abort by themself. It means the
			data of small table is too large to be hold in the memory.
		</description>
	</property>

	<property>
		<name>hive.mapjoin.check.memory.rows</name>
		<value>100000</value>
		<description>The number means after how many rows processed it needs
			to check the memory usage
		</description>
	</property>

	<property>
		<name>hive.auto.convert.join</name>
		<value>false</value>
		<description>Whether Hive enable the optimization about converting
			common join into mapjoin based on the input file size
		</description>
	</property>

	<property>
		<name>hive.auto.convert.join.noconditionaltask</name>
		<value>true</value>
		<description>Whether Hive enable the optimization about converting
			common join into mapjoin based on the input file
			size. If this
			paramater is on, and the sum of size for n-1 of the
			tables/partitions
			for a n-way join is smaller than the
			specified size, the join is
			directly converted to a mapjoin (there is no
			conditional task).
		</description>
	</property>

	<property>
		<name>hive.auto.convert.join.noconditionaltask.size</name>
		<value>10000000</value>
		<description>If hive.auto.convert.join.noconditionaltask is off, this
			parameter does not take affect. However, if it
			is on, and the sum of
			size for n-1 of the tables/partitions for a n-way
			join is smaller than
			this size, the join is directly
			converted to a mapjoin(there is no
			conditional task). The default is 10MB
		</description>
	</property>

	<property>
		<name>hive.optimize.mapjoin.mapreduce</name>
		<value>false</value>
		<description>If hive.auto.convert.join is off, this parameter does not
			take
			affect. If it is on, and if there are map-join jobs followed by a
			map-reduce
			job (for e.g a group by), each map-only job is merged with
			the
			following
			map-reduce job.
		</description>
	</property>

	<property>
		<name>hive.script.auto.progress</name>
		<value>false</value>
		<description>Whether Hive Tranform/Map/Reduce Clause should
			automatically send progress information to TaskTracker to avoid the
			task getting killed because of inactivity. Hive sends progress
			information when the script is outputting to stderr. This option
			removes the need of periodically producing stderr messages, but users
			should be cautious because this may prevent infinite loops in the
			scripts to be killed by TaskTracker.
		</description>
	</property>

	<property>
		<name>hive.script.serde</name>
		<value>org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe</value>
		<description>The default serde for trasmitting input data to and
			reading output data from the user scripts.
		</description>
	</property>

	<property>
		<name>hive.binary.record.max.length</name>
		<value>1000</value>
		<description>Read from a binary stream and treat each
			hive.binary.record.max.length bytes as a record.
			The last record
			before the end of stream can have less than
			hive.binary.record.max.length bytes
		</description>
	</property>


	<property>
		<name>hive.script.recordreader</name>
		<value>org.apache.hadoop.hive.ql.exec.TextRecordReader</value>
		<description>The default record reader for reading data from the user
			scripts.
		</description>
	</property>

	<property>
		<name>hive.script.recordwriter</name>
		<value>org.apache.hadoop.hive.ql.exec.TextRecordWriter</value>
		<description>The default record writer for writing data to the user
			scripts.
		</description>
	</property>

	<property>
		<name>hive.input.format</name>
		<value>org.apache.hadoop.hive.ql.io.CombineHiveInputFormat</value>
		<description>The default input format. Set this to HiveInputFormat if
			you encounter problems with CombineHiveInputFormat.
		</description>
	</property>

	<property>
		<name>hive.udtf.auto.progress</name>
		<value>false</value>
		<description>Whether Hive should automatically send progress
			information to TaskTracker when using UDTF's to prevent the task
			getting killed because of inactivity. Users should be cautious
			because this may prevent TaskTracker from killing tasks with infinte
			loops.
		</description>
	</property>

	<property>
		<name>hive.mapred.reduce.tasks.speculative.execution</name>
		<value>true</value>
		<description>Whether speculative execution for reducers should be
			turned on.
		</description>
	</property>

	<property>
		<name>hive.exec.counters.pull.interval</name>
		<value>1000</value>
		<description>The interval with which to poll the JobTracker for the
			counters the running job. The smaller it is the more load there will
			be on the jobtracker, the higher it is the less granular the caught
			will be.
		</description>
	</property>

	<property>
		<name>hive.querylog.location</name>
		<value>/tmp/${user.name}</value>
		<description>
			Location of Hive run time structured log file
		</description>
	</property>

	<property>
		<name>hive.querylog.enable.plan.progress</name>
		<value>true</value>
		<description>
			Whether to log the plan's progress every time a job's
			progress is checked.
			These logs are written to the location specified
			by
			hive.querylog.location
		</description>
	</property>

	<property>
		<name>hive.querylog.plan.progress.interval</name>
		<value>60000</value>
		<description>
			The interval to wait between logging the plan's progress
			in
			milliseconds.
			If there is a whole number percentage change in the
			progress of the
			mappers or the reducers,
			the progress is logged
			regardless of this value.
			The actual interval will be the ceiling of
			(this value divided by the
			value of
			hive.exec.counters.pull.interval)
			multiplied by the value of hive.exec.counters.pull.interval
			I.e. if it
			is not divide evenly by the value of
			hive.exec.counters.pull.interval
			it will be
			logged less frequently than specified.
			This only has an
			effect if hive.querylog.enable.plan.progress is set to
			true.
		</description>
	</property>

	<property>
		<name>hive.enforce.bucketing</name>
		<value>false</value>
		<description>Whether bucketing is enforced. If true, while inserting
			into the table, bucketing is enforced.
		</description>
	</property>

	<property>
		<name>hive.enforce.sorting</name>
		<value>false</value>
		<description>Whether sorting is enforced. If true, while inserting
			into the table, sorting is enforced.
		</description>
	</property>

	<property>
		<name>hive.optimize.bucketingsorting</name>
		<value>true</value>
		<description>If hive.enforce.bucketing or hive.enforce.sorting is
			true, dont create a reducer for enforcing
			bucketing/sorting for
			queries of the form:
			insert overwrite table T2 select * from T1;
			where
			T1 and T2 are bucketed/sorted by the same keys into the same number
			of buckets.
		</description>
	</property>

	<property>
		<name>hive.enforce.sortmergebucketmapjoin</name>
		<value>false</value>
		<description>If the user asked for sort-merge bucketed map-side join,
			and it cannot be performed,
			should the query fail or not ?
		</description>
	</property>

	<property>
		<name>hive.auto.convert.sortmerge.join</name>
		<value>false</value>
		<description>Will the join be automatically converted to a sort-merge
			join, if the joined tables pass
			the criteria for sort-merge join.
		</description>
	</property>

	<property>
		<name>hive.auto.convert.sortmerge.join.bigtable.selection.policy
		</name>
		<value>org.apache.hadoop.hive.ql.optimizer.AvgPartitionSizeBasedBigTableSelectorForAutoSMJ
		</value>
		<description>The policy to choose the big table for automatic
			conversion to sort-merge join.
			By default, the table with the largest
			partitions is assigned the big
			table. All policies are:
			. based on
			position of the table - the leftmost table is selected
			org.apache.hadoop.hive.ql.optimizer.LeftmostBigTableSMJ.
			. based on
			total size (all the partitions selected in the query) of
			the table
			org.apache.hadoop.hive.ql.optimizer.TableSizeBasedBigTableSelectorForAutoSMJ.
			. based on average size (all the partitions selected in the query) of
			the table
			org.apache.hadoop.hive.ql.optimizer.AvgPartitionSizeBasedBigTableSelectorForAutoSMJ.
			New policies can be added in future.
		</description>
	</property>

	<property>
		<name>hive.metastore.ds.connection.url.hook</name>
		<value></value>
		<description>Name of the hook to use for retriving the JDO connection
			URL. If empty, the value in javax.jdo.option.ConnectionURL is used
		</description>
	</property>

	<property>
		<name>hive.metastore.ds.retry.attempts</name>
		<value>1</value>
		<description>The number of times to retry a metastore call if there
			were a connection error
		</description>
	</property>

	<property>
		<name>hive.metastore.ds.retry.interval</name>
		<value>1000</value>
		<description>The number of miliseconds between metastore retry
			attempts
		</description>
	</property>

	<property>
		<name>hive.metastore.server.min.threads</name>
		<value>200</value>
		<description>Minimum number of worker threads in the Thrift server's
			pool.
		</description>
	</property>

	<property>
		<name>hive.metastore.server.max.threads</name>
		<value>100000</value>
		<description>Maximum number of worker threads in the Thrift server's
			pool.
		</description>
	</property>

	<property>
		<name>hive.metastore.server.tcp.keepalive</name>
		<value>true</value>
		<description>Whether to enable TCP keepalive for the metastore server.
			Keepalive will prevent accumulation of half-open connections.
		</description>
	</property>

	<property>
		<name>hive.metastore.sasl.enabled</name>
		<value>false</value>
		<description>If true, the metastore thrift interface will be secured
			with SASL. Clients must authenticate with Kerberos.
		</description>
	</property>

	<property>
		<name>hive.metastore.thrift.framed.transport.enabled</name>
		<value>false</value>
		<description>If true, the metastore thrift interface will use
			TFramedTransport. When false (default) a standard TTransport is used.
		</description>
	</property>

	<property>
		<name>hive.metastore.kerberos.keytab.file</name>
		<value></value>
		<description>The path to the Kerberos Keytab file containing the
			metastore thrift server's service principal.
		</description>
	</property>

	<property>
		<name>hive.metastore.kerberos.principal</name>
		<value>hive-metastore/_HOST@EXAMPLE.COM</value>
		<description>The service principal for the metastore thrift server.
			The special string _HOST will be replaced automatically with the
			correct host name.
		</description>
	</property>

	<property>
		<name>hive.cluster.delegation.token.store.class</name>
		<value>org.apache.hadoop.hive.thrift.MemoryTokenStore</value>
		<description>The delegation token store implementation. Set to
			org.apache.hadoop.hive.thrift.ZooKeeperTokenStore for load-balanced
			cluster.
		</description>
	</property>

	<property>
		<name>hive.cluster.delegation.token.store.zookeeper.connectString
		</name>
		<value>localhost:2181</value>
		<description>The ZooKeeper token store connect string.</description>
	</property>

	<property>
		<name>hive.cluster.delegation.token.store.zookeeper.znode</name>
		<value>/hive/cluster/delegation</value>
		<description>The root path for token store data.</description>
	</property>

	<property>
		<name>hive.cluster.delegation.token.store.zookeeper.acl</name>
		<value>sasl:hive/host1@EXAMPLE.COM:cdrwa,sasl:hive/host2@EXAMPLE.COM:cdrwa
		</value>
		<description>ACL for token store entries. List comma separated all
			server principals for the cluster.
		</description>
	</property>

	<property>
		<name>hive.metastore.cache.pinobjtypes</name>
		<value>Table,StorageDescriptor,SerDeInfo,Partition,Database,Type,FieldSchema,Order
		</value>
		<description>List of comma separated metastore object types that
			should be pinned in the cache
		</description>
	</property>

	<property>
		<name>hive.optimize.reducededuplication</name>
		<value>true</value>
		<description>Remove extra map-reduce jobs if the data is already
			clustered by the same key which needs to be used again. This should
			always be set to true. Since it is a new feature, it has been made
			configurable.
		</description>
	</property>

	<property>
		<name>hive.optimize.reducededuplication.min.reducer</name>
		<value>4</value>
		<description>Reduce deduplication merges two RSs by moving
			key/parts/reducer-num of the child RS to parent RS.
			That means if
			reducer-num of the child RS is fixed (order by or forced
			bucketing)
			and small, it can make very slow, single MR.
			The optimization will be
			disabled if number of reducers is less than
			specified value.
		</description>
	</property>

	<property>
		<name>hive.exec.dynamic.partition</name>
		<value>true</value>
		<description>Whether or not to allow dynamic partitions in DML/DDL.
		</description>
	</property>

	<property>
		<name>hive.exec.dynamic.partition.mode</name>
		<value>strict</value>
		<description>In strict mode, the user must specify at least one static
			partition in case the user accidentally overwrites all partitions.
		</description>
	</property>

	<property>
		<name>hive.exec.max.dynamic.partitions</name>
		<value>1000</value>
		<description>Maximum number of dynamic partitions allowed to be
			created in total.
		</description>
	</property>

	<property>
		<name>hive.exec.max.dynamic.partitions.pernode</name>
		<value>100</value>
		<description>Maximum number of dynamic partitions allowed to be
			created in each mapper/reducer node.
		</description>
	</property>

	<property>
		<name>hive.exec.max.created.files</name>
		<value>100000</value>
		<description>Maximum number of HDFS files created by all
			mappers/reducers in a MapReduce job.
		</description>
	</property>

	<property>
		<name>hive.exec.default.partition.name</name>
		<value>__HIVE_DEFAULT_PARTITION__</value>
		<description>The default partition name in case the dynamic partition
			column value is null/empty string or anyother values that cannot be
			escaped. This value must not contain any special character used in
			HDFS URI (e.g., ':', '%', '/' etc). The user has to be aware that the
			dynamic partition value should not contain this value to avoid
			confusions.
		</description>
	</property>

	<property>
		<name>hive.stats.dbclass</name>
		<value>jdbc:derby</value>
		<description>The default database that stores temporary hive
			statistics.
		</description>
	</property>

	<property>
		<name>hive.stats.autogather</name>
		<value>true</value>
		<description>A flag to gather statistics automatically during the
			INSERT OVERWRITE command.
		</description>
	</property>

	<property>
		<name>hive.stats.jdbcdriver</name>
		<value>org.apache.derby.jdbc.EmbeddedDriver</value>
		<description>The JDBC driver for the database that stores temporary
			hive statistics.
		</description>
	</property>

	<property>
		<name>hive.stats.dbconnectionstring</name>
		<value>jdbc:derby:;databaseName=TempStatsStore;create=true</value>
		<description>The default connection string for the database that
			stores temporary hive statistics.
		</description>
	</property>

	<property>
		<name>hive.stats.default.publisher</name>
		<value></value>
		<description>The Java class (implementing the StatsPublisher
			interface) that is used by default if hive.stats.dbclass is not JDBC
			or HBase.
		</description>
	</property>

	<property>
		<name>hive.stats.default.aggregator</name>
		<value></value>
		<description>The Java class (implementing the StatsAggregator
			interface) that is used by default if hive.stats.dbclass is not JDBC
			or HBase.
		</description>
	</property>

	<property>
		<name>hive.stats.jdbc.timeout</name>
		<value>30</value>
		<description>Timeout value (number of seconds) used by JDBC connection
			and statements.
		</description>
	</property>

	<property>
		<name>hive.stats.retries.max</name>
		<value>0</value>
		<description>Maximum number of retries when stats publisher/aggregator
			got an exception updating intermediate database. Default is no tries
			on failures.
		</description>
	</property>

	<property>
		<name>hive.stats.retries.wait</name>
		<value>3000</value>
		<description>The base waiting window (in milliseconds) before the next
			retry. The actual wait time is calculated by baseWindow * failues
			baseWindow * (failure 1) * (random number between [0.0,1.0]).
		</description>
	</property>

	<property>
		<name>hive.stats.reliable</name>
		<value>false</value>
		<description>Whether queries will fail because stats cannot be
			collected completely accurately.
			If this is set to true,
			reading/writing from/into a partition may fail
			becuase the stats
			could
			not be computed accurately.
		</description>
	</property>

	<property>
		<name>hive.stats.collect.tablekeys</name>
		<value>false</value>
		<description>Whether join and group by keys on tables are derived and
			maintained in the QueryPlan.
			This is useful to identify how tables are
			accessed and to determine if
			they should be bucketed.
		</description>
	</property>

	<property>
		<name>hive.stats.collect.scancols</name>
		<value>false</value>
		<description>Whether column accesses are tracked in the QueryPlan.
			This is useful to identify how tables are accessed and to determine
			if there are wasted columns that can be trimmed.
		</description>
	</property>

	<property>
		<name>hive.stats.ndv.error</name>
		<value>20.0</value>
		<description>Standard error expressed in percentage. Provides a
			tradeoff between accuracy and compute cost.A lower value for error
			indicates higher accuracy and a higher compute cost.
		</description>
	</property>

	<property>
		<name>hive.stats.key.prefix.max.length</name>
		<value>200</value>
		<description>
			Determines if when the prefix of the key used for
			intermediate stats collection
			exceeds a certain length, a hash of the
			key is used instead. If the
			value &lt; 0 then hashing
			is never used, if
			the value >= 0 then hashing is used only when the key
			prefixes length
			exceeds that value. The key prefix is defined as everything preceding
			the
			task ID in the key.
		</description>
	</property>

	<property>
		<name>hive.support.concurrency</name>
		<value>false</value>
		<description>Whether hive supports concurrency or not. A zookeeper
			instance must be up and running for the default hive lock manager to
			support read-write locks.
		</description>
	</property>

	<property>
		<name>hive.lock.numretries</name>
		<value>100</value>
		<description>The number of times you want to try to get all the locks
		</description>
	</property>

	<property>
		<name>hive.unlock.numretries</name>
		<value>10</value>
		<description>The number of times you want to retry to do one unlock
		</description>
	</property>

	<property>
		<name>hive.lock.sleep.between.retries</name>
		<value>60</value>
		<description>The sleep time (in seconds) between various retries
		</description>
	</property>

	<property>
		<name>hive.zookeeper.quorum</name>
		<value></value>
		<description>The list of zookeeper servers to talk to. This is only
			needed for read/write locks.
		</description>
	</property>

	<property>
		<name>hive.zookeeper.client.port</name>
		<value>2181</value>
		<description>The port of zookeeper servers to talk to. This is only
			needed for read/write locks.
		</description>
	</property>

	<property>
		<name>hive.zookeeper.session.timeout</name>
		<value>600000</value>
		<description>Zookeeper client's session timeout. The client is
			disconnected, and as a result, all locks released, if a heartbeat is
			not sent in the timeout.
		</description>
	</property>

	<property>
		<name>hive.zookeeper.namespace</name>
		<value>hive_zookeeper_namespace</value>
		<description>The parent node under which all zookeeper nodes are
			created.
		</description>
	</property>

	<property>
		<name>hive.zookeeper.clean.extra.nodes</name>
		<value>false</value>
		<description>Clean extra nodes at the end of the session.
		</description>
	</property>

	<property>
		<name>fs.har.impl</name>
		<value>org.apache.hadoop.hive.shims.HiveHarFileSystem</value>
		<description>The implementation for accessing Hadoop Archives. Note
			that this won't be applicable to Hadoop vers less than 0.20
		</description>
	</property>

	<property>
		<name>hive.archive.enabled</name>
		<value>false</value>
		<description>Whether archiving operations are permitted</description>
	</property>

	<property>
		<name>hive.fetch.output.serde</name>
		<value>org.apache.hadoop.hive.serde2.DelimitedJSONSerDe</value>
		<description>The serde used by FetchTask to serialize the fetch
			output.
		</description>
	</property>

	<property>
		<name>hive.exec.mode.local.auto</name>
		<value>false</value>
		<description> Let hive determine whether to run in local mode
			automatically
		</description>
	</property>

	<property>
		<name>hive.exec.drop.ignorenonexistent</name>
		<value>true</value>
		<description>
			Do not report an error if DROP TABLE/VIEW specifies a
			non-existent
			table/view
		</description>
	</property>

	<property>
		<name>hive.exec.show.job.failure.debug.info</name>
		<value>true</value>
		<description>
			If a job fails, whether to provide a link in the CLI to
			the task with
			the
			most failures, along with debugging hints if
			applicable.
		</description>
	</property>

	<property>
		<name>hive.auto.progress.timeout</name>
		<value>0</value>
		<description>
			How long to run autoprogressor for the script/UDTF
			operators (in
			seconds).
			Set to 0 for forever.
		</description>
	</property>

	<!-- HBase Storage Handler Parameters -->

	<property>
		<name>hive.hbase.wal.enabled</name>
		<value>true</value>
		<description>Whether writes to HBase should be forced to the
			write-ahead log. Disabling this improves HBase write performance at
			the risk of lost writes in case of a crash.
		</description>
	</property>

	<property>
		<name>hive.table.parameters.default</name>
		<value></value>
		<description>Default property values for newly created tables
		</description>
	</property>

	<property>
		<name>hive.entity.separator</name>
		<value>@</value>
		<description>Separator used to construct names of tables and
			partitions. For example, dbname@tablename@partitionname
		</description>
	</property>

	<property>
		<name>hive.ddl.createtablelike.properties.whitelist</name>
		<value></value>
		<description>Table Properties to copy over when executing a Create
			Table Like.
		</description>
	</property>

	<property>
		<name>hive.variable.substitute</name>
		<value>true</value>
		<description>This enables substitution using syntax like ${var}
			${system:var} and ${env:var}.
		</description>
	</property>

	<property>
		<name>hive.variable.substitute.depth</name>
		<value>40</value>
		<description>The maximum replacements the substitution engine will do.
		</description>
	</property>

	<property>
		<name>hive.conf.validation</name>
		<value>true</value>
		<description>Eables type checking for registered hive configurations
		</description>
	</property>

	<property>
		<name>hive.security.authorization.enabled</name>
		<value>false</value>
		<description>enable or disable the hive client authorization
		</description>
	</property>

	<property>
		<name>hive.security.authorization.createtable.user.grants</name>
		<value></value>
		<description>the privileges automatically granted to some users
			whenever a table gets created.
			An example like
			"userX,userY:select;userZ:create" will grant select
			privilege to userX
			and userY,
			and grant create privilege to userZ whenever a new table
			created.
		</description>
	</property>

	<property>
		<name>hive.security.authorization.createtable.group.grants</name>
		<value></value>
		<description>the privileges automatically granted to some groups
			whenever a table gets created.
			An example like
			"groupX,groupY:select;groupZ:create" will grant select
			privilege to
			groupX and groupY,
			and grant create privilege to groupZ whenever a new
			table created.
		</description>
	</property>

	<property>
		<name>hive.security.authorization.createtable.role.grants</name>
		<value></value>
		<description>the privileges automatically granted to some roles
			whenever a table gets created.
			An example like
			"roleX,roleY:select;roleZ:create" will grant select
			privilege to roleX
			and roleY,
			and grant create privilege to roleZ whenever a new table
			created.
		</description>
	</property>

	<property>
		<name>hive.security.authorization.createtable.owner.grants</name>
		<value></value>
		<description>the privileges automatically granted to the owner
			whenever a table gets created.
			An example like "select,drop" will
			grant select and drop privilege to
			the owner of the table
		</description>
	</property>

	<property>
		<name>hive.metastore.authorization.storage.checks</name>
		<value>false</value>
		<description>Should the metastore do authorization checks against the
			underlying storage
			for operations like drop-partition (disallow the
			drop-partition if the
			user in
			question doesn't have permissions to
			delete the corresponding directory
			on the storage).
		</description>
	</property>

	<property>
		<name>hive.error.on.empty.partition</name>
		<value>false</value>
		<description>Whether to throw an excpetion if dynamic partition insert
			generates empty results.
		</description>
	</property>

	<property>
		<name>hive.index.compact.file.ignore.hdfs</name>
		<value>false</value>
		<description>True the hdfs location stored in the index file will be
			igbored at runtime.
			If the data got moved or the name of the cluster
			got changed, the index
			data should still be usable.
		</description>
	</property>

	<property>
		<name>hive.optimize.index.filter.compact.minsize</name>
		<value>5368709120</value>
		<description>Minimum size (in bytes) of the inputs on which a compact
			index is automatically used.
		</description>
	</property>

	<property>
		<name>hive.optimize.index.filter.compact.maxsize</name>
		<value>-1</value>
		<description>Maximum size (in bytes) of the inputs on which a compact
			index is automatically used.
			A negative number is equivalent to
			infinity.
		</description>
	</property>

	<property>
		<name>hive.index.compact.query.max.size</name>
		<value>10737418240</value>
		<description>The maximum number of bytes that a query using the
			compact index can read. Negative value is equivalent to infinity.
		</description>
	</property>

	<property>
		<name>hive.index.compact.query.max.entries</name>
		<value>10000000</value>
		<description>The maximum number of index entries to read during a
			query that uses the compact index. Negative value is equivalent to
			infinity.
		</description>
	</property>

	<property>
		<name>hive.index.compact.binary.search</name>
		<value>true</value>
		<description>Whether or not to use a binary search to find the entries
			in an index table that match the filter, where possible
		</description>
	</property>

	<property>
		<name>hive.exim.uri.scheme.whitelist</name>
		<value>hdfs,pfile</value>
		<description>A comma separated list of acceptable URI schemes for
			import and export.
		</description>
	</property>

	<property>
		<name>hive.lock.mapred.only.operation</name>
		<value>false</value>
		<description>This param is to control whether or not only do lock on
			queries
			that need to execute at least one mapred job.
		</description>
	</property>

	<property>
		<name>hive.limit.row.max.size</name>
		<value>100000</value>
		<description>When trying a smaller subset of data for simple LIMIT,
			how much size we need to guarantee
			each row to have at least.
		</description>
	</property>

	<property>
		<name>hive.limit.optimize.limit.file</name>
		<value>10</value>
		<description>When trying a smaller subset of data for simple LIMIT,
			maximum number of files we can
			sample.
		</description>
	</property>

	<property>
		<name>hive.limit.optimize.enable</name>
		<value>false</value>
		<description>Whether to enable to optimization to trying a smaller
			subset of data for simple LIMIT first.
		</description>
	</property>

	<property>
		<name>hive.limit.optimize.fetch.max</name>
		<value>50000</value>
		<description>Maximum number of rows allowed for a smaller subset of
			data for simple LIMIT, if it is a fetch query.
			Insert queries are not
			restricted by this limit.
		</description>
	</property>

	<property>
		<name>hive.rework.mapredwork</name>
		<value>false</value>
		<description>should rework the mapred work or not.
			This is first
			introduced by SymlinkTextInputFormat to replace symlink
			files with
			real paths at compile time.
		</description>
	</property>

	<property>
		<name>hive.exec.concatenate.check.index</name>
		<value>true</value>
		<description>If this sets to true, hive will throw error when doing
			'alter table tbl_name [partSpec] concatenate' on a table/partition
			that has indexes on it. The reason the user want to set this to true
			is because it can help user to avoid handling all index drop,
			recreation,
			rebuild work. This is very helpful for tables with
			thousands of partitions.
		</description>
	</property>

	<property>
		<name>hive.sample.seednumber</name>
		<value>0</value>
		<description>A number used to percentage sampling. By changing this
			number, user will change the subsets
			of data sampled.
		</description>
	</property>

	<property>
		<name>hive.io.exception.handlers</name>
		<value></value>
		<description>A list of io exception handler class names. This is used
			to construct a list exception handlers to handle exceptions thrown
			by
			record readers
		</description>
	</property>

	<property>
		<name>hive.autogen.columnalias.prefix.label</name>
		<value>_c</value>
		<description>String used as a prefix when auto generating column
			alias.
			By default the prefix label will be appended with a column
			position
			number to form the column alias. Auto generation would happen
			if an
			aggregate function is used in a select clause without an
			explicit
			alias.
		</description>
	</property>

	<property>
		<name>hive.autogen.columnalias.prefix.includefuncname</name>
		<value>false</value>
		<description>Whether to include function name in the column alias auto
			generated by hive.
		</description>
	</property>

	<property>
		<name>hive.exec.perf.logger</name>
		<value>org.apache.hadoop.hive.ql.log.PerfLogger</value>
		<description>The class responsible logging client side performance
			metrics. Must be a subclass of
			org.apache.hadoop.hive.ql.log.PerfLogger
		</description>
	</property>

	<property>
		<name>hive.start.cleanup.scratchdir</name>
		<value>false</value>
		<description>To cleanup the hive scratchdir while starting the hive
			server
		</description>
	</property>

	<property>
		<name>hive.output.file.extension</name>
		<value></value>
		<description>String used as a file extension for output files. If not
			set, defaults to the codec extension for text files (e.g. ".gz"), or
			no extension otherwise.
		</description>
	</property>

	<property>
		<name>hive.insert.into.multilevel.dirs</name>
		<value>false</value>
		<description>Where to insert into multilevel directories like
			"insert
			directory '/HIVEFT25686/chinna/' from table"
		</description>
	</property>

	<property>
		<name>hive.warehouse.subdir.inherit.perms</name>
		<value>false</value>
		<description>Set this to true if the the table directories should
			inherit the
			permission of the warehouse or database directory instead
			of being created
			with the permissions derived from dfs umask
		</description>
	</property>

	<property>
		<name>hive.exec.job.debug.capture.stacktraces</name>
		<value>true</value>
		<description>Whether or not stack traces parsed from the task logs of
			a sampled failed task for
			each failed job should be stored in the
			SessionState
		</description>
	</property>

	<property>
		<name>hive.exec.driver.run.hooks</name>
		<value></value>
		<description>A comma separated list of hooks which implement
			HiveDriverRunHook and will be run at the
			beginning and end of
			Driver.run, these will be run in the order specified
		</description>
	</property>

	<property>
		<name>hive.ddl.output.format</name>
		<value>text</value>
		<description>
			The data format to use for DDL output. One of "text" (for
			human
			readable text) or "json" (for a json object).
		</description>
	</property>

	<property>
		<name>hive.transform.escape.input</name>
		<value>false</value>
		<description>
			This adds an option to escape special chars (newlines,
			carriage returns
			and
			tabs) when they are passed to the user script.
			This is useful if the hive
			tables
			can contain data that contains
			special characters.
		</description>
	</property>

	<property>
		<name>hive.exec.rcfile.use.explicit.header</name>
		<value>true</value>
		<description>
			If this is set the header for RC Files will simply be
			RCF. If this is
			not
			set the header will be that borrowed from sequence
			files, e.g. SEQ-
			followed
			by the input and output RC File formats.
		</description>
	</property>

	<property>
		<name>hive.multi.insert.move.tasks.share.dependencies</name>
		<value>false</value>
		<description>
			If this is set all move tasks for tables/partitions (not
			directories)
			at the end of a
			multi-insert query will only begin once
			the dependencies for all these move tasks
			have been
			met.
			Advantages: If
			concurrency is enabled, the locks will only be released once the
			query has
			finished, so with this config enabled, the time when the
			table/partition is
			generated will be much closer to when the lock on
			it is released.
			Disadvantages: If concurrency is not enabled, with
			this disabled, the
			tables/partitions which
			are produced by this query
			and finish earlier will be available for
			querying
			much earlier. Since
			the locks are only released once the query finishes,
			this
			does not
			apply if concurrency is enabled.
		</description>
	</property>

	<property>
		<name>hive.fetch.task.conversion</name>
		<value>minimal</value>
		<description>
			Some select queries can be converted to single FETCH task
			minimizing
			latency.
			Currently the query should be single sourced not
			having any subquery and
			should not have
			any aggregations or distincts
			(which incurrs RS), lateral views and
			joins.
			1. minimal : SELECT STAR,
			FILTER on partition columns, LIMIT only
			2. more : SELECT, FILTER,
			LIMIT only (TABLESAMPLE, virtual columns)
		</description>
	</property>

	<property>
		<name>hive.hmshandler.retry.attempts</name>
		<value>1</value>
		<description>The number of times to retry a HMSHandler call if there
			were a connection error
		</description>
	</property>

	<property>
		<name>hive.hmshandler.retry.interval</name>
		<value>1000</value>
		<description>The number of miliseconds between HMSHandler retry
			attempts
		</description>
	</property>

	<property>
		<name>hive.server.read.socket.timeout</name>
		<value>10</value>
		<description>Timeout for the HiveServer to close the connection if no
			response from the client in N seconds, defaults to 10 seconds.
		</description>
	</property>

	<property>
		<name>hive.server.tcp.keepalive</name>
		<value>true</value>
		<description>Whether to enable TCP keepalive for the Hive server.
			Keepalive will prevent accumulation of half-open connections.
		</description>
	</property>

	<property>
		<name>hive.decode.partition.name</name>
		<value>false</value>
		<description>Whether to show the unquoted partition names in query
			results.
		</description>
	</property>

	<property>
		<name>hive.log4j.file</name>
		<value></value>
		<description>Hive log4j configuration file.
			If the property is not set,
			then logging will be initialized using
			hive-log4j.properties found on
			the classpath.
			If the property is set, the value must be a valid URI
			(java.net.URI,
			e.g. "file:///tmp/my-logging.properties"), which you
			can then extract
			a URL from and pass to
			PropertyConfigurator.configure(URL).
		</description>
	</property>

	<property>
		<name>hive.exec.log4j.file</name>
		<value></value>
		<description>Hive log4j configuration file for execution mode(sub
			command).
			If the property is not set, then logging will be initialized
			using
			hive-exec-log4j.properties found on the classpath.
			If the
			property is set, the value must be a valid URI (java.net.URI,
			e.g.
			"file:///tmp/my-logging.properties"), which you can then extract
			a URL
			from and pass to PropertyConfigurator.configure(URL).
		</description>
	</property>

	<property>
		<name>hive.exec.infer.bucket.sort</name>
		<value>false</value>
		<description>
			If this is set, when writing partitions, the metadata
			will include the
			bucketing/sorting
			properties with which the data was
			written if any (this will not overwrite the
			metadata
			inherited from the
			table if the table is bucketed/sorted)
		</description>
	</property>

	<property>
		<name>hive.exec.infer.bucket.sort.num.buckets.power.two</name>
		<value>false</value>
		<description>
			If this is set, when setting the number of reducers for
			the map reduce
			task which writes the
			final output files, it will choose
			a number which is a power of two,
			unless the user specifies
			the number
			of reducers to use using mapred.reduce.tasks. The number of
			reducers
			may be set to a power of two, only to be followed by a merge task
			meaning preventing
			anything from being inferred.
			With
			hive.exec.infer.bucket.sort set to true:
			Advantages: If this is not
			set, the number of buckets for partitions will seem
			arbitrary,
			which
			means that the number of mappers used for optimized joins, for
			example, will
			be very low. With this set, since the number of buckets
			used for any
			partition is
			a power of two, the number of mappers used
			for optimized joins will be
			the least
			number of buckets used by any
			partition being joined.
			Disadvantages: This may mean a much larger or
			much smaller number of reducers being
			used in the
			final map reduce job,
			e.g. if a job was originally going to take 257
			reducers,
			it will now
			take 512 reducers, similarly if the max number of reducers
			is 511,
			and
			a job was going to use this many, it will now use 256 reducers.

		</description>
	</property>

	<property>
		<name>hive.groupby.orderby.position.alias</name>
		<value>false</value>
		<description>Whether to enable using Column Position Alias in Group By
			or Order By
		</description>
	</property>

	<property>
		<name>hive.server2.thrift.min.worker.threads</name>
		<value>5</value>
		<description>Minimum number of Thrift worker threads</description>
	</property>

	<property>
		<name>hive.server2.thrift.max.worker.threads</name>
		<value>100</value>
		<description>Maximum number of Thrift worker threads</description>
	</property>

	<property>
		<name>hive.server2.thrift.port</name>
		<value>10000</value>
		<description>Port number of HiveServer2 Thrift interface.
			Can be
			overridden by setting $HIVE_SERVER2_THRIFT_PORT
		</description>
	</property>

	<property>
		<name>hive.server2.thrift.bind.host</name>
		<value>localhost</value>
		<description>Bind host on which to run the HiveServer2 Thrift
			interface.
			Can be overridden by setting $HIVE_SERVER2_THRIFT_BIND_HOST
		</description>
	</property>

	<property>
		<name>hive.server2.authentication</name>
		<value>NONE</value>
		<description>
			Client authentication types.
			NONE: no authentication check
			LDAP: LDAP/AD based authentication
			KERBEROS: Kerberos/GSSAPI
			authentication
			CUSTOM: Custom authentication provider
			(Use with
			property hive.server2.custom.authentication.class)
		</description>
	</property>

	<property>
		<name>hive.server2.custom.authentication.class</name>
		<value></value>
		<description>
			Custom authentication class. Used when property
			'hive.server2.authentication' is set to 'CUSTOM'. Provided class
			must
			be a proper implementation of the interface
			org.apache.hive.service.auth.PasswdAuthenticationProvider.
			HiveServer2
			will call its Authenticate(user, passed) method to
			authenticate requests.
			The implementation may optionally extend the
			Hadoop's
			org.apache.hadoop.conf.Configured class to grab Hive's
			Configuration
			object.
		</description>
	</property>

	<property>
		<name>>hive.server2.authentication.kerberos.principal</name>
		<value></value>
		<description>
			Kerberos server principal
		</description>
	</property>

	<property>
		<name>>hive.server2.authentication.kerberos.keytab</name>
		<value></value>
		<description>
			Kerberos keytab file for server principal
		</description>
	</property>

	<property>
		<name>hive.server2.authentication.ldap.url</name>
		<value></value>
		<description>
			LDAP connection URL
		</description>
	</property>

	<property>
		<name>hive.server2.authentication.ldap.baseDN</name>
		<value></value>
		<description>
			LDAP base DN
		</description>
	</property>

	<property>
		<name>hive.server2.enable.doAs</name>
		<value>true</value>
		<description>
			Setting this property to true will have hive server2
			execute
			hive operations as the user making the calls to it.
		</description>
	</property>


</configuration>