[NO ISSUE] Improve handling of udf parameter/return types

- user model changes: yes
- storage format changes: no
- interface changes: no

Details:
- Prohibit parameter/return type specification for inline udfs
- Prohibit parameter/return type quantifier (?) for external udfs
- Allow external udfs to refer to types from other dataverses
- Do not store type quantifiers in udf metadata
- Align names of anonymous types automatically created by
  QueryTranslator for datasets and udfs
- Reserve user-defined type names starting from '$' for system use
- Add testcases
- Prohibit UdfServlet operations if cluster is not active
- Return correct path from IOManager.getWorkspacePath()
- Test framework: support multiple commands in .lib.sqlpp files
- Remove CC files when deleting old instance data in
  AsterixHyracksIntegrationUtil

Change-Id: I09bdfd8c7b26750d12339034d2143a16102d1212
Reviewed-on: https://asterix-gerrit.ics.uci.edu/c/asterixdb/+/6545
Integration-Tests: Jenkins <jenkins@fulliautomatix.ics.uci.edu>
Tested-by: Jenkins <jenkins@fulliautomatix.ics.uci.edu>
Reviewed-by: Dmitry Lychagin <dmitry.lychagin@couchbase.com>
36 files changed
tree: 07680d04036580e0d31b7add278086e4cf860dd1
  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.
  • JDK 11 or newer.
  • Python 3.6+ with pip and venv

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/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.

Documentation

Community support