[NO ISSUE][STO] Fix search when switching from memory to disk component

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

Details:
- When searching the index and making the switch from the memory
  components to the disk components, keep the states of the queue and
  the cursors on the switched-to disk components the same as their
  states were on the memory components. If a cursor was the one who
  produced the outputElement, then do not push the next element into
  the queue from the cursor since there should not be an element in
  the queue from this cursor. Restart the search operation at the
  elements that the cursors were at and consume them since they were
  already consumed before we make the switch.

- add test case.

Change-Id: I647641f6044c1edf1477049be1c5d1b697f404c1
Reviewed-on: https://asterix-gerrit.ics.uci.edu/c/asterixdb/+/14885
Tested-by: Jenkins <jenkins@fulliautomatix.ics.uci.edu>
Integration-Tests: Jenkins <jenkins@fulliautomatix.ics.uci.edu>
Reviewed-by: Murtadha Hubail <mhubail@apache.org>
5 files changed
tree: 056323d5717b41b9f8412f2b852441adcddc23cd
  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
    An expressive and declarative query language (SQL++ that supports 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

To generate the documentation, run asterix-doc with the generate.rr profile in maven, e.g mvn -Pgenerate.rr ... Be sure to run mvn package beforehand or run mvn site in asterix-lang-sqlpp to generate some resources that are used in the documentation that are generated directly from the grammar.

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