[ASTERIXDB-2458][COMP] Fix InjectTypeCastForFunctionArgumentsRule

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

Details:
InjectTypeCastForFunctionArgumentsRule is for functions that
can potentially return any of their arguments. switch and
if_null(expr1, expr2, ...) are examples. All the arguments
need to be casted (opened) to the type that the function
will return which is the generalized type of all arguments.
Some functions like if_null can determine the exact expression
they will return, e.g. if_null(1, {"id": 3}) in which case
the return type is always integer. The rule tries to cast
th 2nd argument, the record, to integer and fails. In such
cases, these functions do not need to cast their arguments.
If the function determines its output type to be ANY, then
all arguments need to be casted (opened). If the function
determines its output to be a dervied type, then casting is
also needed since that output type should be the generalized
type of all arguments.

Change-Id: I2fee234d883b59319e4ec4df58d61ecd498373fd
Reviewed-on: https://asterix-gerrit.ics.uci.edu/3406
Contrib: Jenkins <jenkins@fulliautomatix.ics.uci.edu>
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: Dmitry Lychagin <dmitry.lychagin@couchbase.com>
5 files changed
tree: 934d593fa5b060b66676d89f0a564f830f46ecb3
  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.
  • Oracle JDK 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/apache-asterixdb-*-SNAPSHOT
      $./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.

Documentation

Community support