diff --git a/.travis.yml b/.travis.yml
new file mode 100644
index 0000000..d0e1568
--- /dev/null
+++ b/.travis.yml
@@ -0,0 +1,47 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# https://docs.travis-ci.com/user/ci-environment/
+# trusty - 7.5GB memory and 2 cores
+sudo: required
+dist: trusty
+
+# travis performs a shallow clone by default, in case of any issues
+# that requires full git history, enable this
+# before_install: git fetch --unshallow
+
+# parallel builds on jdk7 and jdk8
+language: java
+jdk:
+ - oraclejdk7
+ - oraclejdk8
+
+cache:
+ directories:
+ - $HOME/.m2
+
+env:
+ MAVEN_SKIP_RC=true
+ MAVEN_OPTS="-Xmx2g -XX:MaxPermSize=512M"
+
+# workaround added: https://github.com/travis-ci/travis-ci/issues/4629
+before_install:
+ - sed -i.bak -e 's|https://nexus.codehaus.org/snapshots/|https://oss.sonatype.org/content/repositories/codehaus-snapshots/|g' ~/.m2/settings.xml
+
+
+install: true
+
+script: mvn clean install -DskipTests -T 4 -q -Pitests
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..f7a4f46
--- /dev/null
+++ b/README.md
@@ -0,0 +1,110 @@
+Apache Hive (TM)
+================
+[](https://travis-ci.org/apache/hive/branches)
+[](http://search.maven.org/#search%7Cga%7C1%7Cg%3A%22org.apache.hive%22)
+
+The Apache Hive (TM) data warehouse software facilitates reading,
+writing, and managing large datasets residing in distributed storage
+using SQL. Built on top of Apache Hadoop (TM), it provides:
+
+* Tools to enable easy access to data via SQL, thus enabling data
+ warehousing tasks such as extract/transform/load (ETL), reporting,
+ and data analysis
+
+* A mechanism to impose structure on a variety of data formats
+
+* Access to files stored either directly in Apache HDFS (TM) or in other
+ data storage systems such as Apache HBase (TM)
+
+* Query execution using Apache Hadoop MapReduce, Apache Tez
+ or Apache Spark frameworks.
+
+Hive provides standard SQL functionality, including many of the later
+2003 and 2011 features for analytics. These include OLAP functions,
+subqueries, common table expressions, and more. Hive's SQL can also be
+extended with user code via user defined functions (UDFs), user defined
+aggregates (UDAFs), and user defined table functions (UDTFs).
+
+Hive users have a choice of 3 runtimes when executing SQL queries.
+Users can choose between Apache Hadoop MapReduce, Apache Tez or
+Apache Spark frameworks as their execution backend. MapReduce is a
+mature framework that is proven at large scales. However, MapReduce
+is a purely batch framework, and queries using it may experience
+higher latencies (tens of seconds), even over small datasets. Apache
+Tez is designed for interactive query, and has substantially reduced
+overheads versus MapReduce. Apache Spark is a cluster computing
+framework that's built outside of MapReduce, but on top of HDFS,
+with a notion of composable and transformable distributed collection
+of items called Resilient Distributed Dataset (RDD) which allows
+processing and analysis without traditional intermediate stages that
+MapReduce introduces.
+
+Users are free to switch back and forth between these frameworks
+at any time. In each case, Hive is best suited for use cases
+where the amount of data processed is large enough to require a
+distributed system.
+
+Hive is not designed for online transaction processing. It is best used
+for traditional data warehousing tasks. Hive is designed to maximize
+scalability (scale out with more machines added dynamically to the Hadoop
+cluster), performance, extensibility, fault-tolerance, and
+loose-coupling with its input formats.
+
+
+General Info
+============
+
+For the latest information about Hive, please visit out website at:
+
+ http://hive.apache.org/
+
+
+Getting Started
+===============
+
+- Installation Instructions and a quick tutorial:
+ https://cwiki.apache.org/confluence/display/Hive/GettingStarted
+
+- A longer tutorial that covers more features of HiveQL:
+ https://cwiki.apache.org/confluence/display/Hive/Tutorial
+
+- The HiveQL Language Manual:
+ https://cwiki.apache.org/confluence/display/Hive/LanguageManual
+
+
+Requirements
+============
+
+- Java 1.7 or 1.8
+
+- Hadoop 1.x, 2.x (2.x required for Hive 2.x)
+
+
+Upgrading from older versions of Hive
+=====================================
+
+- Hive includes changes to the MetaStore schema. If
+ you are upgrading from an earlier version of Hive it is imperative
+ that you upgrade the MetaStore schema by running the appropriate
+ schema upgrade scripts located in the scripts/metastore/upgrade
+ directory.
+
+- We have provided upgrade scripts for MySQL, PostgreSQL, Oracle,
+ Microsoft SQL Server, and Derby databases. If you are using a
+ different database for your MetaStore you will need to provide
+ your own upgrade script.
+
+Useful mailing lists
+====================
+
+1. user@hive.apache.org - To discuss and ask usage questions. Send an
+ empty email to user-subscribe@hive.apache.org in order to subscribe
+ to this mailing list.
+
+2. dev@hive.apache.org - For discussions about code, design and features.
+ Send an empty email to dev-subscribe@hive.apache.org in order to
+ subscribe to this mailing list.
+
+3. commits@hive.apache.org - In order to monitor commits to the source
+ repository. Send an empty email to commits-subscribe@hive.apache.org
+ in order to subscribe to this mailing list.
diff --git a/README.txt b/README.txt
deleted file mode 100644
index 969abde..0000000
--- a/README.txt
+++ /dev/null
@@ -1,108 +0,0 @@
-Apache Hive (TM) @VERSION@
-======================
-
-The Apache Hive (TM) data warehouse software facilitates reading,
-writing, and managing large datasets residing in distributed storage
-using SQL. Built on top of Apache Hadoop (TM), it provides:
-
-* Tools to enable easy access to data via SQL, thus enabling data
- warehousing tasks such as extract/transform/load (ETL), reporting,
- and data analysis
-
-* A mechanism to impose structure on a variety of data formats
-
-* Access to files stored either directly in Apache HDFS (TM) or in other
- data storage systems such as Apache HBase (TM)
-
-* Query execution using Apache Hadoop MapReduce, Apache Tez
- or Apache Spark frameworks.
-
-Hive provides standard SQL functionality, including many of the later
-2003 and 2011 features for analytics. These include OLAP functions,
-subqueries, common table expressions, and more. Hive's SQL can also be
-extended with user code via user defined functions (UDFs), user defined
-aggregates (UDAFs), and user defined table functions (UDTFs).
-
-Hive users have a choice of 3 runtimes when executing SQL queries.
-Users can choose between Apache Hadoop MapReduce, Apache Tez or
-Apache Spark frameworks as their execution backend. MapReduce is a
-mature framework that is proven at large scales. However, MapReduce
-is a purely batch framework, and queries using it may experience
-higher latencies (tens of seconds), even over small datasets. Apache
-Tez is designed for interactive query, and has substantially reduced
-overheads versus MapReduce. Apache Spark is a cluster computing
-framework that's built outside of MapReduce, but on top of HDFS,
-with a notion of composable and transformable distributed collection
-of items called Resilient Distributed Dataset (RDD) which allows
-processing and analysis without traditional intermediate stages that
-MapReduce introduces.
-
-Users are free to switch back and forth between these frameworks
-at any time. In each case, Hive is best suited for use cases
-where the amount of data processed is large enough to require a
-distributed system.
-
-Hive is not designed for online transaction processing. It is best used
-for traditional data warehousing tasks. Hive is designed to maximize
-scalability (scale out with more machines added dynamically to the Hadoop
-cluster), performance, extensibility, fault-tolerance, and
-loose-coupling with its input formats.
-
-
-General Info
-============
-
-For the latest information about Hive, please visit out website at:
-
- http://hive.apache.org/
-
-
-Getting Started
-===============
-
-- Installation Instructions and a quick tutorial:
- https://cwiki.apache.org/confluence/display/Hive/GettingStarted
-
-- A longer tutorial that covers more features of HiveQL:
- https://cwiki.apache.org/confluence/display/Hive/Tutorial
-
-- The HiveQL Language Manual:
- https://cwiki.apache.org/confluence/display/Hive/LanguageManual
-
-
-Requirements
-============
-
-- Java 1.7 or 1.8
-
-- Hadoop 1.x, 2.x (2.x required for Hive 2.x)
-
-
-Upgrading from older versions of Hive
-=====================================
-
-- Hive @VERSION@ includes changes to the MetaStore schema. If
- you are upgrading from an earlier version of Hive it is imperative
- that you upgrade the MetaStore schema by running the appropriate
- schema upgrade scripts located in the scripts/metastore/upgrade
- directory.
-
-- We have provided upgrade scripts for MySQL, PostgreSQL, Oracle,
- Microsoft SQL Server, and Derby databases. If you are using a
- different database for your MetaStore you will need to provide
- your own upgrade script.
-
-Useful mailing lists
-====================
-
-1. user@hive.apache.org - To discuss and ask usage questions. Send an
- empty email to user-subscribe@hive.apache.org in order to subscribe
- to this mailing list.
-
-2. dev@hive.apache.org - For discussions about code, design and features.
- Send an empty email to dev-subscribe@hive.apache.org in order to
- subscribe to this mailing list.
-
-3. commits@hive.apache.org - In order to monitor commits to the source
- repository. Send an empty email to commits-subscribe@hive.apache.org
- in order to subscribe to this mailing list.
diff --git a/pom.xml b/pom.xml
index b05a2dc..9ed1c19 100644
--- a/pom.xml
+++ b/pom.xml
@@ -93,7 +93,7 @@
3.1
1.3.1
2.4
- 2.2
+ 2.4
2.4
2.2
2.19.1