HAWQ-1783. Add GitHub Action Workflow for Build on Linux

- the abs function declared in math.h
- without passing in --dependency=, the bootstrap of libhdfs3 and
  libyarn just search their dependencies in /usr/local/hawq/, which just
  inherits from the default_prefix.

With toolchain.sh provided, it is easy to set up the development env on
both macOS and Linux. And there will be following commits which apply
and test it on Docker images.
7 files changed
tree: 11ff787de2c400e71e7f516ef585e499e0149801
  1. .github/
  2. .gitignore
  3. .travis.yml
  5. GNUmakefile.in
  7. Makefile
  9. README-PostgreSQL
  10. README.md
  11. aclocal.m4
  12. config/
  13. configure
  14. configure.in
  15. contrib/
  16. depends/
  17. dist/
  18. doc/
  19. getversion
  20. licenses/
  21. pom.xml
  22. putversion
  23. pxf/
  24. ranger-plugin/
  25. src/
  26. tools/


CI ProcessStatus
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Apache Release Audit Tool (RAT)Rat Status
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Apache HAWQ

Apache HAWQ is a Hadoop native SQL query engine that combines the key technological advantages of MPP database with the scalability and convenience of Hadoop. HAWQ reads data from and writes data to HDFS natively. HAWQ delivers industry-leading performance and linear scalability. It provides users the tools to confidently and successfully interact with petabyte range data sets. HAWQ provides users with a complete, standards compliant SQL interface. More specifically, HAWQ has the following features:

  • On-premise or cloud deployment
  • Robust ANSI SQL compliance: SQL-92, SQL-99, SQL-2003, OLAP extension
  • Extremely high performance. many times faster than other Hadoop SQL engine
  • World-class parallel optimizer
  • Full transaction capability and consistency guarantee: ACID
  • Dynamic data flow engine through high speed UDP based interconnect
  • Elastic execution engine based on virtual segment & data locality
  • Support multiple level partitioning and List/Range based partitioned tables
  • Multiple compression method support: snappy, gzip, zlib
  • Multi-language user defined function support: Python, Perl, Java, C/C++, R
  • Advanced machine learning and data mining functionalities through MADLib
  • Dynamic node expansion: in seconds
  • Most advanced three level resource management: Integrate with YARN and hierarchical resource queues.
  • Easy access of all HDFS data and external system data (for example, HBase)
  • Hadoop Native: from storage (HDFS), resource management (YARN) to deployment (Ambari).
  • Authentication & Granular authorization: Kerberos, SSL and role based access
  • Advanced C/C++ access library to HDFS and YARN: libhdfs3 & libYARN
  • Support most third party tools: Tableau, SAS et al.
  • Standard connectivity: JDBC/ODBC

Build & Install & Test

Please see HAWQ wiki page: https://cwiki.apache.org/confluence/display/HAWQ/Build+and+Install

Export Control

This distribution includes cryptographic software. The country in which you currently reside may have restrictions on the import, possession, use, and/or re-export to another country, of encryption software. BEFORE using any encryption software, please check your country's laws, regulations and policies concerning the import, possession, or use, and re-export of encryption software, to see if this is permitted. See http://www.wassenaar.org/ for more information.

The U.S. Government Department of Commerce, Bureau of Industry and Security (BIS), has classified this software as Export Commodity Control Number (ECCN) 5D002.C.1, which includes information security software using or performing cryptographic functions with asymmetric algorithms. The form and manner of this Apache Software Foundation distribution makes it eligible for export under the License Exception ENC Technology Software Unrestricted (TSU) exception (see the BIS Export Administration Regulations, Section 740.13) for both object code and source code.