| commit | b893514525f94e9a7688efc16ad35bf2bd6d5f95 | [log] [tgz] |
|---|---|---|
| author | Ali Alsuliman <ali.al.solaiman@gmail.com> | Thu Jan 09 10:54:25 2020 -0800 |
| committer | Ali Alsuliman <ali.al.solaiman@gmail.com> | Fri Jan 10 01:37:50 2020 +0000 |
| tree | fa72072d32fae5cb2fa6aa068c335d0f08ed7eaf | |
| parent | af44111696e833fec220e2c634879a6811407ef5 [diff] |
[ASTERIXDB-2688][HYR] Fix use of a Hyracks task across join stages - user model changes: no - storage format changes: no - interface changes: yes Details: In hash join, a task from the build stage is being used in the probe stage. This is a problem since such tasks have already finished and notified the CC they are done. One observed issue is related to issuing a warning in the probe phase where some warnings are not reported because they are issued to tasks that have finished (the way this happened is that a comparator was created in the build phase using the build-phase task. Then, this comparator was used in the probe phase and issued a warning). - make IHyracksJobletContext extend IHyracksCommonContext so that it is also a frame manager context - make activites of join operators use the joblet context instead of the task context for acquiring buffers - create the probe-to-build comparator in the probe phase so that the right task is used in the comparator Change-Id: I38a4a779b9620494f15606162f0f1e9487fd0984 Reviewed-on: https://asterix-gerrit.ics.uci.edu/c/asterixdb/+/4563 Reviewed-by: Ali Alsuliman <ali.al.solaiman@gmail.com> Reviewed-by: Murtadha Hubail <mhubail@apache.org> Tested-by: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Integration-Tests: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Contrib: Michael Blow <mblow@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/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.