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Installation and Configuration

You can install a stable release of Hive by downloading a tarball, or you can download the source code and build Hive from that.

Running HiveServer2 and Beeline

Requirements

• Java 1.7
  Note:  Hive versions 1.2 onward require Java 1.7 (preferred), or newer. Hive versions 0.14 to 1.1 work with Java 1.6 as well. Users are strongly advised to start moving to Java 1.8 (see HIVE-8607).  
• Hadoop  22.x (preferred), 1.x .  Hive (not supported by Hive 2.0.0 onward).
  Hive versions up to 0.13 also supported Hadoop 0.20.x, 0.23.x.
• Hive is commonly used in production Linux and Windows environment. Mac is a commonly used development environment. The instructions in this document are applicable to Linux and Mac. Using it on Windows would require slightly different steps.  

Installing Hive from a Stable Release

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Building Hive from Source

The Hive SVN GIT repository for the most recent Hive code is located here: httpgit clone https://svngit-wip-us.apache.org/repos/asf/hive/trunk. The repository for branches containing released versions is located here: http://svn.apache.org/repos/asf/hive/branches. All of the .git (the master branch).

All release versions are in subdirectories branches named "branch-0.#" (except or "branch-0.8-r2"); any subdirectories with other names are for 1.#" or the upcoming "branch-2.#", with the exception of release 0.8.1 which is in "branch-0.8-r2". Any branches with other names are feature branches for works-in-progress. See Understanding Hive Branches for details.

As of 0.13, Hive is built using Apache Maven.

Compile Hive on

...

master

To build the current Hive code on Hadoop 0.23 or laterfrom the master branch:

  $ svngit coclone httphttps://svngit-wip-us.apache.org/repos/asf/hive/trunk hive.git
  $ cd hive
  $ mvn clean installpackage -Phadoop-2,distPdist
  $ cd packaging/target/apache-hive-{version}-SNAPSHOT-bin/apache-hive-{version}-SNAPSHOT-bin
  $ ls
  LICENSE
  NOTICE
  README.txt
  RELEASE_NOTES.txt
  bin/ (all the shell scripts)
  lib/ (required jar files)
  conf/ (configuration files)
  examples/ (sample input and query files)
  hcatalog / (hcatalog installation)
  scripts / (upgrade scripts for hive-metastore)

...

If building Hive source using Maven (mvn), we will refer to the directory "/packaging/target/apache-hive-{version}-SNAPSHOT-bin/apache-hive-{version}-SNAPSHOT-bin" as <install-dir> for the rest of the page.

Compile Hive on

...

branch-1

In branch-1, Hive supports both Hadoop 1.x and 2.x.  You will need to specify which version of Hadoop to build against via a Maven profile.  To build against Hadoop 1.x use the profile hadoop-1; for Hadoop 2.x use hadoop-2.  For example to build against Hadoop 1.x, the above mvn command becomesTo build Hive against Hadoop 0.20, build instead with the following Maven profile:

  $ mvn clean installpackage -Phadoop-1,dist

Compile Hive Prior to 0.13 on Hadoop 0.20

Prior to Hive 0.13, Hive was built using Apache Ant.  To build an older version of Hive on Hadoop 0.20:

...

• you must have Hadoop in your path OR
• export HADOOP_HOME=<hadoop-install-dir>

In addition, you must use below HDFS commands to create /tmp and /user/hive/warehouse (aka hive.metastore.warehouse.dir) and set them chmod g+w in HDFS before  before you can create a table in Hive.

Commands to perform this setup:

  $ $HADOOP_HOME/bin/hadoop fs -mkdir       /tmp
  $ $HADOOP_HOME/bin/hadoop fs -mkdir       /user/hive/warehouse
  $ $HADOOP_HOME/bin/hadoop fs -chmod g+w   /tmp
  $ $HADOOP_HOME/bin/hadoop fs -chmod g+w   /user/hive/warehouse

...

  $ export HIVE_HOME=<hive-install-dir>

Running Hive CLI

To use the Hive command line interface (CLI) from the shell:

  $ $HIVE_HOME/bin/hive

Running

...

HiveServer2 and Beeline

Starting from Hive 2.1, we need to run the schematool command below as an initialization step. For example, we can use "derby" as db type. To run the HCatalog server from the shell in Hive release 0.11.0 and later:

  $ $HIVE_HOME/hcatalog/sbin/hcat_server.sh
bin/schematool -dbType <db type> -initSchema

HiveServer2 (introduced in Hive 0.11) has its own CLI called Beeline.  HiveCLI is now deprecated in favor of Beeline, as it lacks the multi-user, security, and other capabilities of HiveServer2.  To run HiveServer2 and Beeline from shellTo use the HCatalog command line interface (CLI) in Hive release 0.11.0 and later:

  $ $HIVE_HOME/hcatalog/bin/hcat

For more information, see HCatalog Installation from Tarball and HCatalog CLI in the HCatalog manual.

Running WebHCat (Templeton)

To run the WebHCat server from the shell in Hive release 0.11.0 and later:

  $ $HIVE_HOME/hcatalog/sbin/webhcat_server.sh

For more information, see WebHCat Installation in the WebHCat manual.

Configuration Management Overview

• Hive by default gets its configuration from <install-dir>/conf/hive-default.xml
• The location of the Hive configuration directory can be changed by setting the HIVE_CONF_DIR environment variable.
• Configuration variables can be changed by (re-)defining them in <install-dir>/conf/hive-site.xml
• Log4j configuration is stored in <install-dir>/conf/hive-log4j.properties

• Hive configuration is an overlay on top of Hadoop – it inherits the Hadoop configuration variables by default.

• Hive configuration can be manipulated by:
  • Editing hive-site.xml and defining any desired variables (including Hadoop variables) in it
  • From the CLI using the set command (see below)
  • Invoking hive using the syntax:
    • $ bin/hive --hiveconf x1=y1 --hiveconf x2=y2
      this sets the variables x1 and x2 to y1 and y2 respectively
  • Setting the HIVE_OPTS environment variable to "--hiveconf x1=y1 --hiveconf x2=y2" which does the same as above.

Runtime Configuration

• Hive queries are executed using map-reduce queries and, therefore, the behavior of such queries can be controlled by the Hadoop configuration variables.

• The CLI command 'SET' can be used to set any Hadoop (or Hive) configuration variable. For example:

  No Format
  hive> SET mapred.job.tracker=myhost.mycompany.com:50030; hive> SET -v;

  The latter shows all the current settings. Without the -v option only the variables that differ from the base Hadoop configuration are displayed.

Hive, Map-Reduce and Local-Mode

Hive compiler generates map-reduce jobs for most queries. These jobs are then submitted to the Map-Reduce cluster indicated by the variable:

  mapred.job.tracker

While this usually points to a map-reduce cluster with multiple nodes, Hadoop also offers a nifty option to run map-reduce jobs locally on the user's workstation. This can be very useful to run queries over small data sets – in such cases local mode execution is usually significantly faster than submitting jobs to a large cluster. Data is accessed transparently from HDFS. Conversely, local mode only runs with one reducer and can be very slow processing larger data sets.

Starting with release 0.7, Hive fully supports local mode execution. To enable this, the user can enable the following option:

  hive> SET mapred.job.tracker=local;

In addition, mapred.local.dir should point to a path that's valid on the local machine (for example /tmp/<username>/mapred/local). (Otherwise, the user will get an exception allocating local disk space.)

Starting with release 0.7, Hive also supports a mode to run map-reduce jobs in local-mode automatically. The relevant options are hive.exec.mode.local.auto, hive.exec.mode.local.auto.inputbytes.max, and hive.exec.mode.local.auto.tasks.max:

  hive> SET hive.exec.mode.local.auto=false;

Note that this feature is disabled by default. If enabled, Hive analyzes the size of each map-reduce job in a query and may run it locally if the following thresholds are satisfied:

• The total input size of the job is lower than: hive.exec.mode.local.auto.inputbytes.max (128MB by default)
• The total number of map-tasks is less than: hive.exec.mode.local.auto.tasks.max (4 by default)
• The total number of reduce tasks required is 1 or 0.

So for queries over small data sets, or for queries with multiple map-reduce jobs where the input to subsequent jobs is substantially smaller (because of reduction/filtering in the prior job), jobs may be run locally.

Note that there may be differences in the runtime environment of Hadoop server nodes and the machine running the Hive client (because of different jvm versions or different software libraries). This can cause unexpected behavior/errors while running in local mode. Also note that local mode execution is done in a separate, child jvm (of the Hive client). If the user so wishes, the maximum amount of memory for this child jvm can be controlled via the option hive.mapred.local.mem. By default, it's set to zero, in which case Hive lets Hadoop determine the default memory limits of the child jvm.

Error Logs

Hive uses log4j for logging. By default logs are not emitted to the console by the CLI. The default logging level is WARN for Hive releases prior to 0.13.0. Starting with Hive 0.13.0, the default logging level is INFO.

The logs are stored in the directory /tmp/<user.name>:

• /tmp/<user.name>/hive.log
  Note: In local mode, prior to Hive 0.13.0 the log file name was ".log" instead of "hive.log". This bug was fixed in release 0.13.0 (see HIVE-5528 and HIVE-5676).

To configure a different log location, set hive.log.dir in $HIVE_HOME/conf/hive-log4j.properties. Make sure the directory has the sticky bit set (chmod 1777 <dir>).

• hive.log.dir=<other_location>

If the user wishes, the logs can be emitted to the console by adding the arguments shown below:

• bin/hive --hiveconf hive.root.logger=INFO,console

Alternatively, the user can change the logging level only by using:

• bin/hive --hiveconf hive.root.logger=INFO,DRFA


Another option for logging is TimeBasedRollingPolicy (Applicable for Hive 0.15.0 and above, HIVE-9001) by providing DAILY option as shown below:

• bin/hive --hiveconf hive.root.logger=INFO,DAILY

Note that setting hive.root.logger via the 'set' command does not change logging properties since they are determined at initialization time.

Hive also stores query logs on a per Hive session basis in /tmp/<user.name>/, but can be configured in hive-site.xml with the hive.querylog.location property.

Logging during Hive execution on a Hadoop cluster is controlled by Hadoop configuration. Usually Hadoop will produce one log file per map and reduce task stored on the cluster machine(s) where the task was executed. The log files can be obtained by clicking through to the Task Details page from the Hadoop JobTracker Web UI.

When using local mode (using mapred.job.tracker=local), Hadoop/Hive execution logs are produced on the client machine itself. Starting with release 0.6 – Hive uses the hive-exec-log4j.properties (falling back to hive-log4j.properties only if it's missing) to determine where these logs are delivered by default. The default configuration file produces one log file per query executed in local mode and stores it under /tmp/<user.name>. The intent of providing a separate configuration file is to enable administrators to centralize execution log capture if desired (on a NFS file server for example). Execution logs are invaluable for debugging run-time errors.

For information about WebHCat errors and logging, see Error Codes and Responses and Log Files in the WebHCat manual.

Error logs are very useful to debug problems. Please send them with any bugs (of which there are many!) to hive-dev@hadoop.apache.org.

Audit Logs

DDL Operations

/bin/hiveserver2

  $ $HIVE_HOME/bin/beeline -u jdbc:hive2://$HS2_HOST:$HS2_PORT

Beeline is started with the JDBC URL of the HiveServer2, which depends on the address and port where HiveServer2 was started.  By default, it will be (localhost:10000), so the address will look like jdbc:hive2://localhost:10000.

Or to start Beeline and HiveServer2 in the same process for testing purpose, for a similar user experience to HiveCLI:

  $ $HIVE_HOME/bin/beeline -u jdbc:hive2://

Running HCatalog

To run the HCatalog server from the shell in Hive release 0.11.0 and later:

  $ $HIVE_HOME/hcatalog/sbin/hcat_server.sh

To use the HCatalog command line interface (CLI) in Hive release 0.11.0 and later:

  $ $HIVE_HOME/hcatalog/bin/hcat

For more information, see HCatalog Installation from Tarball and HCatalog CLI in the HCatalog manual.

Running WebHCat (Templeton)

To run the WebHCat server from the shell in Hive release 0.11.0 and later:

  $ $HIVE_HOME/hcatalog/sbin/webhcat_server.sh

For more information, see WebHCat Installation in the WebHCat manual.

Configuration Management Overview

• Hive by default gets its configuration from <install-dir>/conf/hive-default.xml
• The location of the Hive configuration directory can be changed by setting the HIVE_CONF_DIR environment variable.
• Configuration variables can be changed by (re-)defining them in <install-dir>/conf/hive-site.xml
• Log4j configuration is stored in <install-dir>/conf/hive-log4j.properties

• Hive configuration is an overlay on top of Hadoop – it inherits the Hadoop configuration variables by default.

• Hive configuration can be manipulated by:
  • Editing hive-site.xml and defining any desired variables (including Hadoop variables) in it
  • Using the set command (see next section)
  • Invoking Hive (deprecated), Beeline or HiveServer2 using the syntax:
    • $ bin/hive --hiveconf x1=y1 --hiveconf x2=y2  //this sets the variables x1 and x2 to y1 and y2 respectively
    • $ bin/hiveserver2 --hiveconf x1=y1 --hiveconf x2=y2  //this sets server-side variables x1 and x2 to y1 and y2 respectively
    • $ bin/beeline --hiveconf x1=y1 --hiveconf x2=y2  //this sets client-side variables x1 and x2 to y1 and y2 respectively.
  • Setting the HIVE_OPTS environment variable to "--hiveconf x1=y1 --hiveconf x2=y2" which does the same as above.

Runtime Configuration

• Hive queries are executed using map-reduce queries and, therefore, the behavior of such queries can be controlled by the Hadoop configuration variables.

• The HiveCLI (deprecated) and Beeline command 'SET' can be used to set any Hadoop (or Hive) configuration variable. For example:

  No Format
  beeline> SET mapred.job.tracker=myhost.mycompany.com:50030; beeline> SET -v;

  The latter shows all the current settings. Without the -v option only the variables that differ from the base Hadoop configuration are displayed.

Hive, Map-Reduce and Local-Mode

Hive compiler generates map-reduce jobs for most queries. These jobs are then submitted to the Map-Reduce cluster indicated by the variable:

  mapred.job.tracker

While this usually points to a map-reduce cluster with multiple nodes, Hadoop also offers a nifty option to run map-reduce jobs locally on the user's workstation. This can be very useful to run queries over small data sets – in such cases local mode execution is usually significantly faster than submitting jobs to a large cluster. Data is accessed transparently from HDFS. Conversely, local mode only runs with one reducer and can be very slow processing larger data sets.

Starting with release 0.7, Hive fully supports local mode execution. To enable this, the user can enable the following option:

  hive> SET mapreduce.framework.name=local;

In addition, mapred.local.dir should point to a path that's valid on the local machine (for example /tmp/<username>/mapred/local). (Otherwise, the user will get an exception allocating local disk space.)

Starting with release 0.7, Hive also supports a mode to run map-reduce jobs in local-mode automatically. The relevant options are hive.exec.mode.local.auto, hive.exec.mode.local.auto.inputbytes.max, and hive.exec.mode.local.auto.tasks.max:

  hive> SET hive.exec.mode.local.auto=false;

Note that this feature is disabled by default. If enabled, Hive analyzes the size of each map-reduce job in a query and may run it locally if the following thresholds are satisfied:

• The total input size of the job is lower than: hive.exec.mode.local.auto.inputbytes.max (128MB by default)
• The total number of map-tasks is less than: hive.exec.mode.local.auto.tasks.max (4 by default)
• The total number of reduce tasks required is 1 or 0.

So for queries over small data sets, or for queries with multiple map-reduce jobs where the input to subsequent jobs is substantially smaller (because of reduction/filtering in the prior job), jobs may be run locally.

Note that there may be differences in the runtime environment of Hadoop server nodes and the machine running the Hive client (because of different jvm versions or different software libraries). This can cause unexpected behavior/errors while running in local mode. Also note that local mode execution is done in a separate, child jvm (of the Hive client). If the user so wishes, the maximum amount of memory for this child jvm can be controlled via the option hive.mapred.local.mem. By default, it's set to zero, in which case Hive lets Hadoop determine the default memory limits of the child jvm.

Hive Logging

Anchor
Error Logs Error Logs

Anchor
Hive Logs Hive Logs

Hive uses log4j for logging. By default logs are not emitted to the console by the CLI. The default logging level is WARN for Hive releases prior to 0.13.0. Starting with Hive 0.13.0, the default logging level is INFO.

The logs are stored in the directory /tmp/<user.name>:

• /tmp/<user.name>/hive.log
  Note: In local mode, prior to Hive 0.13.0 the log file name was ".log" instead of "hive.log". This bug was fixed in release 0.13.0 (see HIVE-5528 and HIVE-5676).

To configure a different log location, set hive.log.dir in $HIVE_HOME/conf/hive-log4j.properties. Make sure the directory has the sticky bit set (chmod 1777 <dir>).

• hive.log.dir=<other_location>

If the user wishes, the logs can be emitted to the console by adding the arguments shown below:

• bin/hive --hiveconf hive.root.logger=INFO,console  //for HiveCLI (deprecated)
• bin/hiveserver2 --hiveconf hive.root.logger=INFO,console

Alternatively, the user can change the logging level only by using:

• bin/hive --hiveconf hive.root.logger=INFO,DRFA //for HiveCLI (deprecated)

• bin/hiveserver2 --hiveconf hive.root.logger=INFO,DRFA


Another option for logging is TimeBasedRollingPolicy (applicable for Hive 1.1.0 and above, HIVE-9001) by providing DAILY option as shown below:

• bin/hive --hiveconf hive.root.logger=INFO,DAILY //for HiveCLI (deprecated)
• bin/hiveserver2 --hiveconf hive.root.logger=INFO,DAILY

Note that setting hive.root.logger via the 'set' command does not change logging properties since they are determined at initialization time.

Hive also stores query logs on a per Hive session basis in /tmp/<user.name>/, but can be configured in hive-site.xml with the hive.querylog.location property.  Starting with Hive 1.1.0, EXPLAIN EXTENDED output for queries can be logged at the INFO level by setting the hive.log.explain.output property to true.

Logging during Hive execution on a Hadoop cluster is controlled by Hadoop configuration. Usually Hadoop will produce one log file per map and reduce task stored on the cluster machine(s) where the task was executed. The log files can be obtained by clicking through to the Task Details page from the Hadoop JobTracker Web UI.

When using local mode (using mapreduce.framework.name=local), Hadoop/Hive execution logs are produced on the client machine itself. Starting with release 0.6 – Hive uses the hive-exec-log4j.properties (falling back to hive-log4j.properties only if it's missing) to determine where these logs are delivered by default. The default configuration file produces one log file per query executed in local mode and stores it under /tmp/<user.name>. The intent of providing a separate configuration file is to enable administrators to centralize execution log capture if desired (on a NFS file server for example). Execution logs are invaluable for debugging run-time errors.

For information about WebHCat errors and logging, see Error Codes and Responses and Log Files in the WebHCat manual.

Error logs are very useful to debug problems. Please send them with any bugs (of which there are many!) to hive-dev@hadoop.apache.org.

From Hive 2.1.0 onwards (with HIVE-13027), Hive uses Log4j2's asynchronous logger by default. Setting hive.async.log.enabled to false will disable asynchronous logging and fallback to synchronous logging. Asynchronous logging can give significant performance improvement as logging will be handled in a separate thread that uses the LMAX disruptor queue for buffering log messages. Refer to https://logging.apache.org/log4j/2.x/manual/async.html for benefits and drawbacks.

HiveServer2 Logs

HiveServer2 operation logs are available to clients starting in Hive 0.14. See HiveServer2 Logging for configuration.

Audit Logs

Audit logs are logged from the Hive metastore server for every metastore API invocation.

An audit log has the function and some of the relevant function arguments logged in the metastore log file. It is logged at the INFO level of log4j, so you need to make sure that the logging at the INFO level is enabled (see HIVE-3505). The name of the log entry is "HiveMetaStore.audit".

Audit logs were added in Hive 0.7 for secure client connections (HIVE-1948) and in Hive 0.10 for non-secure connections (HIVE-3277; also see HIVE-2797).

Perf Logger

In order to obtain the performance metrics via the PerfLogger, you need to set DEBUG level logging for the PerfLogger class (HIVE-12675). This can be achieved by setting the following in the log4j properties file.

log4j.logger.org.apache.hadoop.hive.ql.log.PerfLogger=DEBUG

If the logger level has already been set to DEBUG at root via hive.root.logger, the above setting is not required to see the performance logs.

DDL Operations

 The Hive DDL operations are The Hive DDL operations are documented in Hive Data Definition Language.

Creating Hive Tables

  hive> CREATE TABLE pokes (foo INT, bar STRING);

...