| commit | 865a2ed0b594802c8ad93acf26e533b9377b3a47 | [log] [tgz] |
|---|---|---|
| author | Murtadha Hubail <mhubail@apache.org> | Tue Aug 28 15:38:22 2018 +0300 |
| committer | Murtadha Hubail <mhubail@apache.org> | Tue Aug 28 15:42:50 2018 -0700 |
| tree | 8dd4be0ed310289b1420112c34fa220f791982e0 | |
| parent | c410e83270947af25b5dc373cbf9c8d74a0789a0 [diff] |
[ASTERIXDB-2444][STO] Avoid Using System Clock in Storage - user model changes: no - storage format changes: yes - interface changes: yes Details: - Replace the usage of system clock timestamps in LSM index components file names by a sequencer. The next sequence id to use is determined by checking the list of existing components on disk. Note that due to a rollback, an index checkpoint file may have last valid component sequence which is greater than what is on disk. This should not cause any issues since only components that have a sequence greater than that appears in the checkpoint will be deleted. - Replace the usage of system clock timestamps in LSM index components ids by a monotonically increasing sequencer. The sequencer is initialized after restarts by the last valid component id that appears in the index checkpoint. - Refactor the logic to generate flush/merge file names. - Refactor the logic to check invalid components. - Adapt test cases to new naming format. Change-Id: I9dff8ffb38ce8064a199d03b070ed1f5b924b8a4 Reviewed-on: https://asterix-gerrit.ics.uci.edu/2927 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: Murtadha Hubail <mhubail@apache.org> Reviewed-by: abdullah alamoudi <bamousaa@gmail.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/ $./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.