Feed Connection Refactoring

1. The feed subscription network using FeedJoint is removed.
2. FeedConnection metadata dataset is added (pkeys: dataverseName,
   feedName, datasetName).
3. Replaced the old intake job + collect job combination with one single
   job using SplitOperator.
4. Now one feed can connect to multiple datasets.
5. The disconnect feed job is replaced by ActiveManagerMessage.
6. The new feed life cycle is:
   - Create feed
   - Connect feed to dataset0, dataset1, dataset2, etc.
   - Start feed
   - Stop feed
   - Disconnect feed
 7. New feedEventListner framework by Abdullah

Change-Id: Ic36267eb9a10df21734ce1cc1f38583e23c9e8f0
Reviewed-on: https://asterix-gerrit.ics.uci.edu/1259
Tested-by: Jenkins <jenkins@fulliautomatix.ics.uci.edu>
Reviewed-by: Till Westmann <tillw@apache.org>
Integration-Tests: Jenkins <jenkins@fulliautomatix.ics.uci.edu>
Reviewed-by: abdullah alamoudi <bamousaa@gmail.com>
195 files changed
tree: e17222c7d6fd0aa4554cc926282ff1afdd2a95b4
  1. .gitattributes
  2. .gitignore
  3. README.md
  4. asterixdb/
  5. build.xml
  6. hyracks-fullstack/
  7. pom.xml
README.md

What is AsterixDB?

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.

Build from source

To build AsterixDB from source, you should have a platform with the following:

  • A Unix-ish environment (Linux, OS X, will all do).
  • git
  • Maven 3.3.9 or newer.
  • Java 8 or newer.

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
    

Run the build on your machine

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.

Documentation

master | 0.9.0

Community support