| commit | 01423da8a2c006706a89e21e852799eae33d35ef | [log] [tgz] |
|---|---|---|
| author | Ali Alsuliman <ali.al.solaiman@gmail.com> | Mon Jun 10 13:25:32 2019 -0700 |
| committer | Dmitry Lychagin <dmitry.lychagin@couchbase.com> | Mon Jun 10 23:25:34 2019 +0000 |
| tree | 1223756801a57e33ae1dd312b08744670ed505c8 | |
| parent | f9725e4bfa463c13fe78dc66994038e0c8d702c2 [diff] |
[ASTERIXDB-2458][COMP] Fix min/max functions with group by - user model changes: no - storage format changes: no - interface changes: no Details: In a sort-group-by operator, an aggregate function has a merging aggregate function that will be used when merging the run files if they were generated. The merging aggregate function of the local min/max aggregate function should be different from the merging aggregate function of the global min/max. For local min/max, the merging aggregate function should propagate system_null if the aggregation is system_null. Also, the global min/max should handle finishPartial() different from finish(). finishPartial() should not output NULL if the aggregation is system_null since the aggregation is still going on. - added functions to be intermediate steps for local aggregation. - implemented logic for finishPartial() - added test cases for strict_min/max with group by Change-Id: Ie0551b091b9adbbbd51158dbd36124a7184bdce0 Reviewed-on: https://asterix-gerrit.ics.uci.edu/3434 Contrib: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Sonar-Qube: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Tested-by: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Integration-Tests: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Reviewed-by: Ali Alsuliman <ali.al.solaiman@gmail.com> Reviewed-by: Dmitry Lychagin <dmitry.lychagin@couchbase.com>
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/apache-asterixdb-*-SNAPSHOT $./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.