HAWQ-1277. Fix build problem on CentOS 7, with --with-plperl.

See earlier discussion on this on pgsql-hackers, message-id
9B946296-A2EB-4B45-A190-153F06662F8B@kineticode.com. We'd get this fix
eventually as we merge with later PostgreSQL versions, but let's make life
easier for people hitting this issue now.

This is a backpatch of the following upstream commit, sans the MSVC build
parts, as I have no environment to test that and we don't support Windows
anyway. We'll get the MSVC parts later, as we merge.

commit ba00ab0b111a0cbbac612e8ea8b0d5f96534102e
Author: Andrew Dunstan <andrew@dunslane.net>
Date:   Sat Nov 26 15:22:32 2011 -0500

    Use the preferred version of xsubpp, not necessarily the one that came with the
    distro version of perl.

    David Wheeler and Alex Hunsaker.

    Backpatch to 9.1 where it applies cleanly. A simple workaround is available for earlier
    branches, and further effort doesn't seem warranted.
1 file changed
tree: bed3d6282618dc62fa189861b158771f7724e5e0
  1. .gitignore
  2. .travis.yml
  4. GNUmakefile.in
  6. Makefile
  8. README-PostgreSQL
  9. README.md
  10. aclocal.m4
  11. config/
  12. configure
  13. configure.in
  14. contrib/
  15. depends/
  16. doc/
  17. getversion
  18. licenses/
  19. pom.xml
  20. putversion
  21. pxf/
  22. src/
  23. tools/

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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

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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.