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Posted to commits@hawq.apache.org by rl...@apache.org on 2015/11/11 03:35:26 UTC
incubator-hawq git commit: HAWQ-143. Add informations in Apache-HAWQ
README.md
Repository: incubator-hawq
Updated Branches:
refs/heads/master e24233fa2 -> 5401b1045
HAWQ-143. Add informations in Apache-HAWQ README.md
Project: http://git-wip-us.apache.org/repos/asf/incubator-hawq/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-hawq/commit/5401b104
Tree: http://git-wip-us.apache.org/repos/asf/incubator-hawq/tree/5401b104
Diff: http://git-wip-us.apache.org/repos/asf/incubator-hawq/diff/5401b104
Branch: refs/heads/master
Commit: 5401b10452f513587e3c0bf02486b5c153424b39
Parents: e24233f
Author: stanlyxiang <st...@gmail.com>
Authored: Tue Nov 10 16:30:59 2015 +0800
Committer: stanlyxiang <st...@gmail.com>
Committed: Tue Nov 10 16:30:59 2015 +0800
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README.md | 27 +++++++++++++++++++++++++++
1 file changed, 27 insertions(+)
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http://git-wip-us.apache.org/repos/asf/incubator-hawq/blob/5401b104/README.md
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diff --git a/README.md b/README.md
index 1379f5d..22b690c 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,28 @@
# 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, quicklz, RLE
+ - 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 refer to the [BUILD_INSTRUCTIONS][1] file.
+
+ [1]: https://github.com/apache/incubator-hawq/blob/master/BUILD_INSTRUCTIONS.md "BUILD_INSTRUCTIONS"