| commit | d292d99bc652e81ae1e7877e88529ce2b29cf6d0 | [log] [tgz] |
|---|---|---|
| author | Ali Alsuliman <ali.al.solaiman@gmail.com> | Fri Sep 06 00:21:36 2019 -0700 |
| committer | Ali Alsuliman <ali.al.solaiman@gmail.com> | Fri Sep 06 23:42:00 2019 +0000 |
| tree | 5efb19efb482b1ce86eed7cd2ff82cbf72172b9f | |
| parent | cba9cbe380e04a183caadc13497c97d0db6ff31c [diff] |
[NO ISSUE][COMP] Fix index selection for datasets with meta
- user model changes: no
- storage format changes: no
- interface changes: no
Details:
Fix index selection for datasets with meta. Access method rule should
check where the field is coming from (dataset record or meta record)
and then determine if the field matches the keys in the index based
on their names and sources.
This patch also fixes resolving PK field accesses to the primary key
variable (e.g. $ds.getField("id") is turned into $13 where id is a PK).
The fix considers whether the PK is coming from the data record or the
meta record.
The patch also includes fixing rewriting of meta() references and
replacing them with their corresponding meta variables. Now nested plans
are visited also when looking for meta() references to take care of cases
where the data scan producing the meta variable and the meta() references
happen to be inside the nested plans.
MetaFunctionToMetaVariable() is fired also after the rules which eliminate
subplans to allow for rewriting of the meta() if it couldn't be replaced
when the meta() reference was in the subplan but referring to meta variable
outside the nested plan.
ReinferAllTypesRule() is now fired before ByNameToByIndexFieldAccessRule()
to allow the latter rule to get the up-to-date types in the whole plan.
Change-Id: I0503f64cd51153896e2d7d7abc465c679f82e2fd
Reviewed-on: https://asterix-gerrit.ics.uci.edu/3545
Tested-by: Jenkins <jenkins@fulliautomatix.ics.uci.edu>
Integration-Tests: Jenkins <jenkins@fulliautomatix.ics.uci.edu>
Reviewed-by: Dmitry Lychagin <dmitry.lychagin@couchbase.com>
Contrib: Till Westmann <tillw@apache.org>
AsterixDB is a BDMS (Big Data Management System) with a rich feature set that sets it apart from other Big Data platforms. Its feature set makes it well-suited to modern needs such as web data warehousing and social data storage and analysis. AsterixDB has:
Data model
A semistructured NoSQL style data model (ADM) resulting from extending JSON with object database ideas
Query languages
Two expressive and declarative query languages (SQL++ and AQL) that support a broad range of queries and analysis over semistructured data
Scalability
A parallel runtime query execution engine, Apache Hyracks, that has been scale-tested on up to 1000+ cores and 500+ disks
Native storage
Partitioned LSM-based data storage and indexing to support efficient ingestion and management of semistructured data
External storage
Support for query access to externally stored data (e.g., data in HDFS) as well as to data stored natively by AsterixDB
Data types
A rich set of primitive data types, including spatial and temporal data in addition to integer, floating point, and textual data
Indexing
Secondary indexing options that include B+ trees, R trees, and inverted keyword (exact and fuzzy) index types
Transactions
Basic transactional (concurrency and recovery) capabilities akin to those of a NoSQL store
Learn more about AsterixDB at its website.
To build AsterixDB from source, you should have a platform with the following:
Instructions for building the master:
Checkout AsterixDB master:
$git clone https://github.com/apache/asterixdb.git
Build AsterixDB master:
$cd asterixdb $mvn clean package -DskipTests
Here are steps to get AsterixDB running on your local machine:
Start a single-machine AsterixDB instance:
$cd asterixdb/asterix-server/target/asterix-server-*-binary-assembly/ $./opt/local/bin/start-sample-cluster.sh
Good to go and run queries in your browser at:
http://localhost:19001
Read more documentation to learn the data model, query language, and how to create a cluster instance.