| commit | 8f1cd017b710c6de4bf5f1b480f8daaeb06de388 | [log] [tgz] |
|---|---|---|
| author | luochen <cluo8@uci.edu> | Thu Dec 17 13:40:55 2020 -0800 |
| committer | Murtadha Hubail <mhubail@apache.org> | Thu Mar 25 20:38:31 2021 +0000 |
| tree | 54c56d17384d51306a2463930438f30463b97655 | |
| parent | 30d8fcbe3475aa4b1e1c6a742ac071d0b8f9bc38 [diff] |
[ASTERIXDB-2813] Limit the number of flush/merge threads - user model changes: no - storage format changes: no - interface changes: yes. Details: - Limit the number of flush/merge threads by introducing the following parameters. - storage.max.running.flushes.per.partition: the maximum number of running flushes for each partition. - storage.max.scheduled.merge.per.partition: the maximum number of scheduled merges for each partition. This is mainly used by the greedy scheduler. - storage.max.running.merges.per.partition: the maximum number of running mergese per partition. - Basically, we limit the number of flush/merge threads and put newly created flush/merge opreations into a wait queue if the limit is reached. - For the greedy scheduler, the scheduled merges (i.e., merge threads) are more than the running merges so that the scheduler can pick the smallest merge for each LSM-tree. Change-Id: I85a55423a1438b1d534c2e6a5968e675a99884c8 Reviewed-on: https://asterix-gerrit.ics.uci.edu/c/asterixdb/+/9183 Integration-Tests: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Reviewed-by: Murtadha Hubail <mhubail@apache.org> Tested-by: Murtadha Hubail <mhubail@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:19006
Read more documentation to learn the data model, query language, and how to create a cluster instance.
To generate the documentation, run asterix-doc with the generate.rr profile in maven, e.g mvn -Pgenerate.rr ... Be sure to run mvn package beforehand or run mvn site in asterix-lang-sqlpp to generate some resources that are used in the documentation that are generated directly from the grammar.