commit | b4d166b3ca042ce34d737f5d2a4fb758fa45d3e5 | [log] [tgz] |
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author | Abdullah Alamoudi <bamousaa@gmail.com> | Sun Dec 17 11:34:33 2017 +0300 |
committer | abdullah alamoudi <bamousaa@gmail.com> | Sun Dec 17 05:00:40 2017 -0800 |
tree | 54d102e45c950c32f155b709eb160646643596b5 | |
parent | 26cc908022eb5d7a2569560c5490ce30a4ac922b [diff] |
[ASTERIXDB-2194][COMP] Introduce datasource functions - user model changes: yes Some functions can be datasources - storage format changes: no - interface changes: yes - Add IDatasourceFunction: A function that is also a datasource - Add IFunctionToDataSourceTransformer: transform an unnest function into a datascan during compilation Details: - Currently, functions are location agnostic and are run on parameters that are either passed through them during compile time or runtime. - An exception to this is the dataset function which has an associated location constraints running on the nodes which host the dataset. - In this change, we introduce a general framework that allows creation of new functions similar to the dataset function. - Such functions are called datasource Functions. - A datasource function takes constant parameters and run on a set of partitions similar to the dataset function. - The first example of such functions is the DatasetResources function. - The DatasetResources function takes two parameters, a dataverse and a dataset. It is then run on all nodes and returns a set of dataset resources. - Test cases are added for this function. Change-Id: Ibcf807ac713a21e8f4d59868525467386e801303 Reviewed-on: https://asterix-gerrit.ics.uci.edu/2216 Sonar-Qube: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Integration-Tests: Jenkins <jenkins@fulliautomatix.ics.uci.edu> Reviewed-by: abdullah alamoudi <bamousaa@gmail.com> Tested-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 documentations to learn the data model, query language, and how to create a cluster instance.