| commit | 05365fd0639c14eed80bfbe67ae3f24fef72228a | [log] [tgz] |
|---|---|---|
| author | Abdullah Alamoudi <bamousaa@gmail.com> | Wed Feb 21 08:20:39 2018 -0800 |
| committer | abdullah alamoudi <bamousaa@gmail.com> | Wed Feb 21 09:53:09 2018 -0800 |
| tree | f10466d35306e2ae0a9f06e44ca079d7d8063941 | |
| parent | fdf862eacb58b233abe2f98b60b467457e243176 [diff] |
[NO ISSUE][TXN] Prevent deadlock in Metadata transactions - user model changes: no - storage format changes: no - interface changes: no Details: - Flushes in metadata datasets are triggerred by entity update logs, unlike regular transactions where flushes are triggerred by entity commit logs. - Because entity update logs can be writting to disk before the operation completes, there is a chance that an operation that caused the component to be full exits after the log is flushed and so, a flush operation is not scheduled. - This change proposes a simple fix. The fix is that metadata operation will also check if a flush is needed and will schedule one if needed. Change-Id: I07a18840dc54fe052b7bd294595f816f6d8a4d2f Reviewed-on: https://asterix-gerrit.ics.uci.edu/2413 Sonar-Qube: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Reviewed-by: Murtadha Hubail <mhubail@apache.org> Tested-by: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Contrib: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Integration-Tests: Jenkins <jenkins@fulliautomatix.ics.uci.edu>
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 documentations to learn the data model, query language, and how to create a cluster instance.