| commit | 7e76a0797388d5c8f92a96c7fa6b4cf30c0886f0 | [log] [tgz] |
|---|---|---|
| author | Xikui Wang <xkkwww@gmail.com> | Fri Oct 20 13:12:30 2017 -0700 |
| committer | Xikui Wang <xkkwww@gmail.com> | Sat Oct 21 09:10:23 2017 -0700 |
| tree | 1e9d5229584ad4e654490fa5132cab72d42d1281 | |
| parent | 799046dfaaa97e30758ab77e3974d00c1a1ed017 [diff] |
[ASTERIXDB-1983] Feed pipeline refactoring for SQL++ - user model changes: no - storage format changes: no - interface changes: no Current implementation of feed uses handcraft AQL queries for creating feed pipeline. This causes a lot of issues and does not support SQL++ very well. Also, there is an overhead for parsing the query everytime. In this patch, it's replaced with compiled statement in SQL++ which provides support for attaching UDF to feed as well. Details: 1. Remove SubscribeFeedStatement. 2. Remove SubscribeFeed related query compilation code, and reuse the upsert dataflow. 3. Added SQL++ User Defined Function support for feed, including adding multiple functions to one feed. 4. Related test cases added. 5. Change the default behavior of feed to be upsert instead of upsert. 'insert-feed' option is provided for experiment uses. 6. This patch also fixes several feed related bugs: [ASTERIXDB-2085] [ASTERIXDB-2124]. Change-Id: I0ae5a837613780a4d2c90c98139fdc6d5e040cc9 Reviewed-on: https://asterix-gerrit.ics.uci.edu/2059 Sonar-Qube: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Tested-by: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Contrib: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Reviewed-by: abdullah alamoudi <bamousaa@gmail.com> 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.