<description>reads outside of transactions</description>
</property>
<property>
<name>javax.jdo.option.ConnectionUserName</name>
<value>APP</value>
<description>username to use against metastore database</description>
</property>
<property>
<name>javax.jdo.option.ConnectionPassword</name>
<value>mine</value>
<description>password to use against metastore database</description>
</property>
<property>
<name>javax.jdo.option.Multithreaded</name>
<value>true</value>
<description>Set this to true if multiple threads access metastore through JDO concurrently.</description>
</property>
<property>
<name>datanucleus.connectionPoolingType</name>
<value>DBCP</value>
<description>Uses a DBCP connection pool for JDBC metastore</description>
</property>
<property>
<name>datanucleus.validateTables</name>
<value>false</value>
<description>validates existing schema against code. turn this on if you want to verify existing schema </description>
</property>
<property>
<name>datanucleus.validateColumns</name>
<value>false</value>
<description>validates existing schema against code. turn this on if you want to verify existing schema </description>
</property>
<property>
<name>datanucleus.validateConstraints</name>
<value>false</value>
<description>validates existing schema against code. turn this on if you want to verify existing schema </description>
</property>
<property>
<name>datanucleus.storeManagerType</name>
<value>rdbms</value>
<description>metadata store type</description>
</property>
<property>
<name>datanucleus.autoCreateSchema</name>
<value>true</value>
<description>creates necessary schema on a startup if one doesn't exist. set this to false, after creating it once</description>
</property>
<property>
<name>datanucleus.autoStartMechanismMode</name>
<value>checked</value>
<description>throw exception if metadata tables are incorrect</description>
</property>
<property>
<name>datanucleus.transactionIsolation</name>
<value>read-committed</value>
<description>Default transaction isolation level for identity generation. </description>
</property>
<property>
<name>datanucleus.cache.level2</name>
<value>false</value>
<description>Use a level 2 cache. Turn this off if metadata is changed independently of hive metastore server</description>
</property>
<property>
<name>datanucleus.cache.level2.type</name>
<value>SOFT</value>
<description>SOFT=soft reference based cache, WEAK=weak reference based cache.</description>
</property>
<property>
<name>datanucleus.identifierFactory</name>
<value>datanucleus</value>
<description>Name of the identifier factory to use when generating table/column names etc. 'datanucleus' is used for backward compatibility</description>
<description>Defines what happens when plugin bundles are found and are duplicated [EXCEPTION|LOG|NONE]</description>
</property>
<property>
<name>hive.metastore.warehouse.dir</name>
<value>/user/hive/warehouse</value>
<description>location of default database for the warehouse</description>
</property>
<property>
<name>hive.metastore.execute.setugi</name>
<value>false</value>
<description>In unsecure mode, setting this property to true will cause the metastore to execute DFS operations using the client's reported user and group permissions. Note that this property must be set on both the client and server sides. Further note that its best effort. If client sets its to true and server sets it to false, client setting will be ignored.</description>
</property>
<property>
<name>hive.metastore.event.listeners</name>
<value></value>
<description>list of comma seperated listeners for metastore events.</description>
<description>list of comma seperated keys occurring in table properties which will get inherited to newly created partitions. * implies all the keys will get inherited.</description>
</property>
<property>
<name>hive.metadata.export.location</name>
<value></value>
<description>When used in conjunction with the org.apache.hadoop.hive.ql.parse.MetaDataExportListener pre event listener, it is the location to which the metadata will be exported. The default is an empty string, which results in the metadata being exported to the current user's home directory on HDFS.</description>
<description>When used in conjunction with the org.apache.hadoop.hive.ql.parse.MetaDataExportListener pre event listener, this setting determines if the metadata that is exported will subsequently be moved to the user's trash directory alongside the dropped table data. This ensures that the metadata will be cleaned up along with the dropped table data.</description>
<description>Partition names will be checked against this regex pattern and rejected if not matched. To use, enable hive.metastore.pre.event.listeners=org.apache.hadoop.hive.metastore.PartitionNameWhitelistPreEventListener Listener will not register if this property value is empty.</description>
<description>Name of the class that implements org.apache.hadoop.hive.metastore.rawstore interface. This class is used to store and retrieval of raw metadata objects such as table, database</description>
</property>
<property>
<name>hive.metastore.batch.retrieve.max</name>
<value>300</value>
<description>Maximum number of objects (tables/partitions) can be retrieved from metastore in one batch. The higher the number, the less the number of round trips is needed to the Hive metastore server, but it may also cause higher memory requirement at the client side.</description>
<description>Maximum number of table partitions that metastore internally retrieves in one batch.</description>
</property>
<property>
<name>hive.default.fileformat</name>
<value>TextFile</value>
<description>Default file format for CREATE TABLE statement. Options are TextFile and SequenceFile. Users can explicitly say CREATE TABLE ... STORED AS <TEXTFILE|SEQUENCEFILE> to override</description>
</property>
<property>
<name>hive.fileformat.check</name>
<value>true</value>
<description>Whether to check file format or not when loading data files</description>
</property>
<property>
<name>hive.map.aggr</name>
<value>true</value>
<description>Whether to use map-side aggregation in Hive Group By queries</description>
</property>
<property>
<name>hive.groupby.skewindata</name>
<value>false</value>
<description>Whether there is skew in data to optimize group by queries</description>
</property>
<property>
<name>hive.groupby.mapaggr.checkinterval</name>
<value>100000</value>
<description>Number of rows after which size of the grouping keys/aggregation classes is performed</description>
</property>
<property>
<name>hive.mapred.local.mem</name>
<value>0</value>
<description>For local mode, memory of the mappers/reducers</description>
<description>The max memory to be used by map-side grup aggregation hash table, if the memory usage is higher than this number, force to flush data</description>
</property>
<property>
<name>hive.map.aggr.hash.percentmemory</name>
<value>0.5</value>
<description>Portion of total memory to be used by map-side grup aggregation hash table</description>
</property>
<property>
<name>hive.map.aggr.hash.min.reduction</name>
<value>0.5</value>
<description>Hash aggregation will be turned off if the ratio between hash
table size and input rows is bigger than this number. Set to 1 to make sure
hash aggregation is never turned off.</description>
</property>
<property>
<name>hive.optimize.cp</name>
<value>true</value>
<description>Whether to enable column pruner</description>
</property>
<property>
<name>hive.optimize.index.filter</name>
<value>false</value>
<description>Whether to enable automatic use of indexes</description>
</property>
<property>
<name>hive.optimize.index.groupby</name>
<value>false</value>
<description>Whether to enable optimization of group-by queries using Aggregate indexes.</description>
</property>
<property>
<name>hive.optimize.ppd</name>
<value>true</value>
<description>Whether to enable predicate pushdown</description>
</property>
<property>
<name>hive.optimize.ppd.storage</name>
<value>true</value>
<description>Whether to push predicates down into storage handlers. Ignored when hive.optimize.ppd is false.</description>
</property>
<property>
<name>hive.ppd.recognizetransivity</name>
<value>true</value>
<description>Whether to transitively replicate predicate filters over equijoin conditions.</description>
</property>
<property>
<name>hive.optimize.groupby</name>
<value>true</value>
<description>Whether to enable the bucketed group by from bucketed partitions/tables.</description>
</property>
<property>
<name>hive.optimize.skewjoin.compiletime</name>
<value>false</value>
<description>Whether to create a separate plan for skewed keys for the tables in the join.
This is based on the skewed keys stored in the metadata. At compile time, the plan is broken
into different joins: one for the skewed keys, and the other for the remaining keys. And then,
a union is performed for the 2 joins generated above. So unless the same skewed key is present
in both the joined tables, the join for the skewed key will be performed as a map-side join.
The main difference between this paramater and hive.optimize.skewjoin is that this parameter
uses the skew information stored in the metastore to optimize the plan at compile time itself.
If there is no skew information in the metadata, this parameter will not have any affect.
Both hive.optimize.skewjoin.compiletime and hive.optimize.skewjoin should be set to true.
Ideally, hive.optimize.skewjoin should be renamed as hive.optimize.skewjoin.runtime, but not doing
so for backward compatibility.
If the skew information is correctly stored in the metadata, hive.optimize.skewjoin.compiletime
would change the query plan to take care of it, and hive.optimize.skewjoin will be a no-op.
</description>
</property>
<property>
<name>hive.optimize.union.remove</name>
<value>false</value>
<description>
Whether to remove the union and push the operators between union and the filesink above
union. This avoids an extra scan of the output by union. This is independently useful for union
queries, and specially useful when hive.optimize.skewjoin.compiletime is set to true, since an
extra union is inserted.
The merge is triggered if either of hive.merge.mapfiles or hive.merge.mapredfiles is set to true.
If the user has set hive.merge.mapfiles to true and hive.merge.mapredfiles to false, the idea was the
number of reducers are few, so the number of files anyway are small. However, with this optimization,
we are increasing the number of files possibly by a big margin. So, we merge aggresively.
</description>
</property>
<property>
<name>hive.mapred.supports.subdirectories</name>
<value>false</value>
<description>Whether the version of hadoop which is running supports sub-directories for tables/partitions.
Many hive optimizations can be applied if the hadoop version supports sub-directories for
tables/partitions. It was added by MAPREDUCE-1501
</description>
</property>
<property>
<name>hive.multigroupby.singlemr</name>
<value>false</value>
<description>Whether to optimize multi group by query to generate single M/R
job plan. If the multi group by query has common group by keys, it will be
optimized to generate single M/R job.</description>
</property>
<property>
<name>hive.map.groupby.sorted</name>
<value>false</value>
<description>If the bucketing/sorting properties of the table exactly match the grouping key, whether to
perform the group by in the mapper by using BucketizedHiveInputFormat. The only downside to this
is that it limits the number of mappers to the number of files.
</description>
</property>
<property>
<name>hive.join.emit.interval</name>
<value>1000</value>
<description>How many rows in the right-most join operand Hive should buffer before emitting the join result. </description>
</property>
<property>
<name>hive.join.cache.size</name>
<value>25000</value>
<description>How many rows in the joining tables (except the streaming table) should be cached in memory. </description>
</property>
<property>
<name>hive.mapjoin.bucket.cache.size</name>
<value>100</value>
<description>How many values in each keys in the map-joined table should be cached in memory. </description>
</property>
<property>
<name>hive.mapjoin.cache.numrows</name>
<value>25000</value>
<description>How many rows should be cached by jdbm for map join. </description>
</property>
<property>
<name>hive.optimize.skewjoin</name>
<value>false</value>
<description>Whether to enable skew join optimization.
The algorithm is as follows: At runtime, detect the keys with a large skew. Instead of
processing those keys, store them temporarily in a hdfs directory. In a follow-up map-reduce
job, process those skewed keys. The same key need not be skewed for all the tables, and so,
the follow-up map-reduce job (for the skewed keys) would be much faster, since it would be a
Note: This config won't impact users if they don't list bucketing.
</description>
</property>
<property>
<name>hive.skewjoin.key</name>
<value>100000</value>
<description>Determine if we get a skew key in join. If we see more
than the specified number of rows with the same key in join operator,
we think the key as a skew join key. </description>
</property>
<property>
<name>hive.skewjoin.mapjoin.map.tasks</name>
<value>10000</value>
<description> Determine the number of map task used in the follow up map join job
for a skew join. It should be used together with hive.skewjoin.mapjoin.min.split
to perform a fine grained control.</description>
</property>
<property>
<name>hive.skewjoin.mapjoin.min.split</name>
<value>33554432</value>
<description> Determine the number of map task at most used in the follow up map join job
for a skew join by specifying the minimum split size. It should be used together with
hive.skewjoin.mapjoin.map.tasks to perform a fine grained control.</description>
</property>
<property>
<name>hive.mapred.mode</name>
<value>nonstrict</value>
<description>The mode in which the hive operations are being performed.
In strict mode, some risky queries are not allowed to run. They include:
Cartesian Product.
No partition being picked up for a query.
Comparing bigints and strings.
Comparing bigints and doubles.
Orderby without limit.
</description>
</property>
<property>
<name>hive.enforce.bucketmapjoin</name>
<value>false</value>
<description>If the user asked for bucketed map-side join, and it cannot be performed,
should the query fail or not ? For eg, if the buckets in the tables being joined are
not a multiple of each other, bucketed map-side join cannot be performed, and the
query will fail if hive.enforce.bucketmapjoin is set to true.
</description>
</property>
<property>
<name>hive.exec.script.maxerrsize</name>
<value>100000</value>
<description>Maximum number of bytes a script is allowed to emit to standard error (per map-reduce task). This prevents runaway scripts from filling logs partitions to capacity </description>
<description> When enabled, this option allows a user script to exit successfully without consuming all the data from the standard input.
</description>
</property>
<property>
<name>hive.script.operator.id.env.var</name>
<value>HIVE_SCRIPT_OPERATOR_ID</value>
<description> Name of the environment variable that holds the unique script operator ID in the user's transform function (the custom mapper/reducer that the user has specified in the query)
</description>
</property>
<property>
<name>hive.script.operator.truncate.env</name>
<value>false</value>
<description>Truncate each environment variable for external script in scripts operator to 20KB (to fit system limits)</description>
</property>
<property>
<name>hive.exec.compress.output</name>
<value>false</value>
<description> This controls whether the final outputs of a query (to a local/hdfs file or a hive table) is compressed. The compression codec and other options are determined from hadoop config variables mapred.output.compress* </description>
</property>
<property>
<name>hive.exec.compress.intermediate</name>
<value>false</value>
<description> This controls whether intermediate files produced by hive between multiple map-reduce jobs are compressed. The compression codec and other options are determined from hadoop config variables mapred.output.compress* </description>
</property>
<property>
<name>hive.exec.parallel</name>
<value>false</value>
<description>Whether to execute jobs in parallel</description>
</property>
<property>
<name>hive.exec.parallel.thread.number</name>
<value>8</value>
<description>How many jobs at most can be executed in parallel</description>
</property>
<property>
<name>hive.exec.rowoffset</name>
<value>false</value>
<description>Whether to provide the row offset virtual column</description>
</property>
<property>
<name>hive.task.progress</name>
<value>false</value>
<description>Whether Hive should periodically update task progress counters during execution. Enabling this allows task progress to be monitored more closely in the job tracker, but may impose a performance penalty. This flag is automatically set to true for jobs with hive.exec.dynamic.partition set to true.</description>
</property>
<property>
<name>hive.hwi.war.file</name>
<value>lib/hive-hwi-0.10.0.war</value>
<description>This sets the path to the HWI war file, relative to ${HIVE_HOME}. </description>
</property>
<property>
<name>hive.hwi.listen.host</name>
<value>0.0.0.0</value>
<description>This is the host address the Hive Web Interface will listen on</description>
</property>
<property>
<name>hive.hwi.listen.port</name>
<value>9999</value>
<description>This is the port the Hive Web Interface will listen on</description>
</property>
<property>
<name>hive.exec.pre.hooks</name>
<value></value>
<description>Comma-separated list of pre-execution hooks to be invoked for each statement. A pre-execution hook is specified as the name of a Java class which implements the org.apache.hadoop.hive.ql.hooks.ExecuteWithHookContext interface.</description>
</property>
<property>
<name>hive.exec.post.hooks</name>
<value></value>
<description>Comma-separated list of post-execution hooks to be invoked for each statement. A post-execution hook is specified as the name of a Java class which implements the org.apache.hadoop.hive.ql.hooks.ExecuteWithHookContext interface.</description>
</property>
<property>
<name>hive.exec.failure.hooks</name>
<value></value>
<description>Comma-separated list of on-failure hooks to be invoked for each statement. An on-failure hook is specified as the name of Java class which implements the org.apache.hadoop.hive.ql.hooks.ExecuteWithHookContext interface.</description>
</property>
<property>
<name>hive.client.stats.publishers</name>
<value></value>
<description>Comma-separated list of statistics publishers to be invoked on counters on each job. A client stats publisher is specified as the name of a Java class which implements the org.apache.hadoop.hive.ql.stats.ClientStatsPublisher interface.</description>
</property>
<property>
<name>hive.client.stats.counters</name>
<value></value>
<description>Subset of counters that should be of interest for hive.client.stats.publishers (when one wants to limit their publishing). Non-display names should be used</description>
</property>
<property>
<name>hive.merge.mapfiles</name>
<value>true</value>
<description>Merge small files at the end of a map-only job</description>
</property>
<property>
<name>hive.merge.mapredfiles</name>
<value>false</value>
<description>Merge small files at the end of a map-reduce job</description>
</property>
<property>
<name>hive.mergejob.maponly</name>
<value>true</value>
<description>Try to generate a map-only job for merging files if CombineHiveInputFormat is supported.</description>
</property>
<property>
<name>hive.heartbeat.interval</name>
<value>1000</value>
<description>Send a heartbeat after this interval - used by mapjoin and filter operators</description>
</property>
<property>
<name>hive.merge.size.per.task</name>
<value>256000000</value>
<description>Size of merged files at the end of the job</description>
</property>
<property>
<name>hive.merge.smallfiles.avgsize</name>
<value>16000000</value>
<description>When the average output file size of a job is less than this number, Hive will start an additional map-reduce job to merge the output files into bigger files. This is only done for map-only jobs if hive.merge.mapfiles is true, and for map-reduce jobs if hive.merge.mapredfiles is true.</description>
</property>
<property>
<name>hive.mapjoin.smalltable.filesize</name>
<value>25000000</value>
<description>The threshold for the input file size of the small tables; if the file size is smaller than this threshold, it will try to convert the common join into map join</description>
<description>This number means how much memory the local task can take to hold the key/value into in-memory hash table; If the local task's memory usage is more than this number, the local task will be abort by themself. It means the data of small table is too large to be hold in the memory.</description>
<description>This number means how much memory the local task can take to hold the key/value into in-memory hash table when this map join followed by a group by; If the local task's memory usage is more than this number, the local task will be abort by themself. It means the data of small table is too large to be hold in the memory.</description>
</property>
<property>
<name>hive.mapjoin.check.memory.rows</name>
<value>100000</value>
<description>The number means after how many rows processed it needs to check the memory usage</description>
</property>
<property>
<name>hive.auto.convert.join</name>
<value>false</value>
<description>Whether Hive enable the optimization about converting common join into mapjoin based on the input file size</description>
</property>
<property>
<name>hive.script.auto.progress</name>
<value>false</value>
<description>Whether Hive Tranform/Map/Reduce Clause should automatically send progress information to TaskTracker to avoid the task getting killed because of inactivity. Hive sends progress information when the script is outputting to stderr. This option removes the need of periodically producing stderr messages, but users should be cautious because this may prevent infinite loops in the scripts to be killed by TaskTracker. </description>
<description>The default input format. Set this to HiveInputFormat if you encounter problems with CombineHiveInputFormat.</description>
</property>
<property>
<name>hive.udtf.auto.progress</name>
<value>false</value>
<description>Whether Hive should automatically send progress information to TaskTracker when using UDTF's to prevent the task getting killed because of inactivity. Users should be cautious because this may prevent TaskTracker from killing tasks with infinte loops. </description>
<description>Whether speculative execution for reducers should be turned on. </description>
</property>
<property>
<name>hive.exec.counters.pull.interval</name>
<value>1000</value>
<description>The interval with which to poll the JobTracker for the counters the running job. The smaller it is the more load there will be on the jobtracker, the higher it is the less granular the caught will be.</description>
</property>
<property>
<name>hive.querylog.location</name>
<value>/tmp/${user.name}</value>
<description>
Location of Hive run time structured log file
</description>
</property>
<property>
<name>hive.querylog.enable.plan.progress</name>
<value>true</value>
<description>
Whether to log the plan's progress every time a job's progress is checked.
These logs are written to the location specified by hive.querylog.location
</description>
</property>
<property>
<name>hive.querylog.plan.progress.interval</name>
<value>60000</value>
<description>
The interval to wait between logging the plan's progress in milliseconds.
If there is a whole number percentage change in the progress of the mappers or the reducers,
the progress is logged regardless of this value.
The actual interval will be the ceiling of (this value divided by the value of
hive.exec.counters.pull.interval) multiplied by the value of hive.exec.counters.pull.interval
I.e. if it is not divide evenly by the value of hive.exec.counters.pull.interval it will be
logged less frequently than specified.
This only has an effect if hive.querylog.enable.plan.progress is set to true.
</description>
</property>
<property>
<name>hive.enforce.bucketing</name>
<value>false</value>
<description>Whether bucketing is enforced. If true, while inserting into the table, bucketing is enforced. </description>
</property>
<property>
<name>hive.enforce.sorting</name>
<value>false</value>
<description>Whether sorting is enforced. If true, while inserting into the table, sorting is enforced. </description>
</property>
<property>
<name>hive.enforce.sortmergebucketmapjoin</name>
<value>false</value>
<description>If the user asked for sort-merge bucketed map-side join, and it cannot be performed,
<description>Name of the hook to use for retriving the JDO connection URL. If empty, the value in javax.jdo.option.ConnectionURL is used </description>
</property>
<property>
<name>hive.metastore.ds.retry.attempts</name>
<value>1</value>
<description>The number of times to retry a metastore call if there were a connection error</description>
</property>
<property>
<name>hive.metastore.ds.retry.interval</name>
<value>1000</value>
<description>The number of miliseconds between metastore retry attempts</description>
</property>
<property>
<name>hive.metastore.server.min.threads</name>
<value>200</value>
<description>Minimum number of worker threads in the Thrift server's pool.</description>
</property>
<property>
<name>hive.metastore.server.max.threads</name>
<value>100000</value>
<description>Maximum number of worker threads in the Thrift server's pool.</description>
</property>
<property>
<name>hive.metastore.server.tcp.keepalive</name>
<value>true</value>
<description>Whether to enable TCP keepalive for the metastore server. Keepalive will prevent accumulation of half-open connections.</description>
</property>
<property>
<name>hive.metastore.sasl.enabled</name>
<value>false</value>
<description>If true, the metastore thrift interface will be secured with SASL. Clients must authenticate with Kerberos.</description>
<description>If true, the metastore thrift interface will use TFramedTransport. When false (default) a standard TTransport is used.</description>
</property>
<property>
<name>hive.metastore.kerberos.keytab.file</name>
<value></value>
<description>The path to the Kerberos Keytab file containing the metastore thrift server's service principal.</description>
</property>
<property>
<name>hive.metastore.kerberos.principal</name>
<value>hive-metastore/_HOST@EXAMPLE.COM</value>
<description>The service principal for the metastore thrift server. The special string _HOST will be replaced automatically with the correct host name.</description>
<description>The delegation token store implementation. Set to org.apache.hadoop.hive.thrift.ZooKeeperTokenStore for load-balanced cluster.</description>
<description>List of comma separated metastore object types that should be pinned in the cache</description>
</property>
<property>
<name>hive.optimize.reducededuplication</name>
<value>true</value>
<description>Remove extra map-reduce jobs if the data is already clustered by the same key which needs to be used again. This should always be set to true. Since it is a new feature, it has been made configurable.</description>
</property>
<property>
<name>hive.exec.dynamic.partition</name>
<value>true</value>
<description>Whether or not to allow dynamic partitions in DML/DDL.</description>
</property>
<property>
<name>hive.exec.dynamic.partition.mode</name>
<value>strict</value>
<description>In strict mode, the user must specify at least one static partition in case the user accidentally overwrites all partitions.</description>
</property>
<property>
<name>hive.exec.max.dynamic.partitions</name>
<value>1000</value>
<description>Maximum number of dynamic partitions allowed to be created in total.</description>
<description>Maximum number of dynamic partitions allowed to be created in each mapper/reducer node.</description>
</property>
<property>
<name>hive.exec.max.created.files</name>
<value>100000</value>
<description>Maximum number of HDFS files created by all mappers/reducers in a MapReduce job.</description>
</property>
<property>
<name>hive.exec.default.partition.name</name>
<value>__HIVE_DEFAULT_PARTITION__</value>
<description>The default partition name in case the dynamic partition column value is null/empty string or anyother values that cannot be escaped. This value must not contain any special character used in HDFS URI (e.g., ':', '%', '/' etc). The user has to be aware that the dynamic partition value should not contain this value to avoid confusions.</description>
</property>
<property>
<name>hive.stats.dbclass</name>
<value>jdbc:derby</value>
<description>The default database that stores temporary hive statistics.</description>
</property>
<property>
<name>hive.stats.autogather</name>
<value>true</value>
<description>A flag to gather statistics automatically during the INSERT OVERWRITE command.</description>
<description>The default connection string for the database that stores temporary hive statistics.</description>
</property>
<property>
<name>hive.stats.default.publisher</name>
<value></value>
<description>The Java class (implementing the StatsPublisher interface) that is used by default if hive.stats.dbclass is not JDBC or HBase.</description>
</property>
<property>
<name>hive.stats.default.aggregator</name>
<value></value>
<description>The Java class (implementing the StatsAggregator interface) that is used by default if hive.stats.dbclass is not JDBC or HBase.</description>
</property>
<property>
<name>hive.stats.jdbc.timeout</name>
<value>30</value>
<description>Timeout value (number of seconds) used by JDBC connection and statements.</description>
</property>
<property>
<name>hive.stats.retries.max</name>
<value>0</value>
<description>Maximum number of retries when stats publisher/aggregator got an exception updating intermediate database. Default is no tries on failures.</description>
</property>
<property>
<name>hive.stats.retries.wait</name>
<value>3000</value>
<description>The base waiting window (in milliseconds) before the next retry. The actual wait time is calculated by baseWindow * failues + baseWindow * (failure + 1) * (random number between [0.0,1.0]).</description>
</property>
<property>
<name>hive.stats.reliable</name>
<value>false</value>
<description>Whether queries will fail because stats cannot be collected completely accurately.
If this is set to true, reading/writing from/into a partition may fail becuase the stats
could not be computed accurately.
</description>
</property>
<property>
<name>hive.stats.collect.tablekeys</name>
<value>false</value>
<description>Whether join and group by keys on tables are derived and maintained in the QueryPlan.
This is useful to identify how tables are accessed and to determine if they should be bucketed.
</description>
</property>
<property>
<name>hive.stats.ndv.error</name>
<value>20.0</value>
<description>Standard error expressed in percentage. Provides a tradeoff between accuracy and compute cost.A lower value for error indicates higher accuracy and a higher compute cost.
</description>
</property>
<property>
<name>hive.support.concurrency</name>
<value>false</value>
<description>Whether hive supports concurrency or not. A zookeeper instance must be up and running for the default hive lock manager to support read-write locks.</description>
</property>
<property>
<name>hive.lock.numretries</name>
<value>100</value>
<description>The number of times you want to try to get all the locks</description>
</property>
<property>
<name>hive.unlock.numretries</name>
<value>10</value>
<description>The number of times you want to retry to do one unlock</description>
</property>
<property>
<name>hive.lock.sleep.between.retries</name>
<value>60</value>
<description>The sleep time (in seconds) between various retries</description>
</property>
<property>
<name>hive.zookeeper.quorum</name>
<value></value>
<description>The list of zookeeper servers to talk to. This is only needed for read/write locks.</description>
</property>
<property>
<name>hive.zookeeper.client.port</name>
<value>2181</value>
<description>The port of zookeeper servers to talk to. This is only needed for read/write locks.</description>
</property>
<property>
<name>hive.zookeeper.session.timeout</name>
<value>600000</value>
<description>Zookeeper client's session timeout. The client is disconnected, and as a result, all locks released, if a heartbeat is not sent in the timeout.</description>
</property>
<property>
<name>hive.zookeeper.namespace</name>
<value>hive_zookeeper_namespace</value>
<description>The parent node under which all zookeeper nodes are created.</description>
</property>
<property>
<name>hive.zookeeper.clean.extra.nodes</name>
<value>false</value>
<description>Clean extra nodes at the end of the session.</description>
If a job fails, whether to provide a link in the CLI to the task with the
most failures, along with debugging hints if applicable.
</description>
</property>
<property>
<name>hive.auto.progress.timeout</name>
<value>0</value>
<description>
How long to run autoprogressor for the script/UDTF operators (in seconds).
Set to 0 for forever.
</description>
</property>
<!-- HBase Storage Handler Parameters -->
<property>
<name>hive.hbase.wal.enabled</name>
<value>true</value>
<description>Whether writes to HBase should be forced to the write-ahead log. Disabling this improves HBase write performance at the risk of lost writes in case of a crash.</description>
</property>
<property>
<name>hive.table.parameters.default</name>
<value></value>
<description>Default property values for newly created tables</description>
</property>
<property>
<name>hive.entity.separator</name>
<value>@</value>
<description>Separator used to construct names of tables and partitions. For example, dbname@tablename@partitionname</description>
<description>Maximum size (in bytes) of the inputs on which a compact index is automatically used.
A negative number is equivalent to infinity.</description>
</property>
<property>
<name>hive.index.compact.query.max.size</name>
<value>10737418240</value>
<description>The maximum number of bytes that a query using the compact index can read. Negative value is equivalent to infinity.</description>
</property>
<property>
<name>hive.index.compact.query.max.entries</name>
<value>10000000</value>
<description>The maximum number of index entries to read during a query that uses the compact index. Negative value is equivalent to infinity.</description>
</property>
<property>
<name>hive.index.compact.binary.search</name>
<value>true</value>
<description>Whether or not to use a binary search to find the entries in an index table that match the filter, where possible</description>
</property>
<property>
<name>hive.exim.uri.scheme.whitelist</name>
<value>hdfs,pfile</value>
<description>A comma separated list of acceptable URI schemes for import and export.</description>
</property>
<property>
<name>hive.lock.mapred.only.operation</name>
<value>false</value>
<description>This param is to control whether or not only do lock on queries
that need to execute at least one mapred job.</description>
</property>
<property>
<name>hive.limit.row.max.size</name>
<value>100000</value>
<description>When trying a smaller subset of data for simple LIMIT, how much size we need to guarantee
each row to have at least.</description>
</property>
<property>
<name>hive.limit.optimize.limit.file</name>
<value>10</value>
<description>When trying a smaller subset of data for simple LIMIT, maximum number of files we can
sample.</description>
</property>
<property>
<name>hive.limit.optimize.enable</name>
<value>false</value>
<description>Whether to enable to optimization to trying a smaller subset of data for simple LIMIT first.</description>
</property>
<property>
<name>hive.limit.optimize.fetch.max</name>
<value>50000</value>
<description>Maximum number of rows allowed for a smaller subset of data for simple LIMIT, if it is a fetch query.
Insert queries are not restricted by this limit.</description>
</property>
<property>
<name>hive.rework.mapredwork</name>
<value>false</value>
<description>should rework the mapred work or not.
This is first introduced by SymlinkTextInputFormat to replace symlink files with real paths at compile time.</description>
</property>
<property>
<name>hive.exec.concatenate.check.index</name>
<value>true</value>
<description>If this sets to true, hive will throw error when doing
'alter table tbl_name [partSpec] concatenate' on a table/partition
that has indexes on it. The reason the user want to set this to true
is because it can help user to avoid handling all index drop, recreation,
rebuild work. This is very helpful for tables with thousands of partitions.</description>
</property>
<property>
<name>hive.sample.seednumber</name>
<value>0</value>
<description>A number used to percentage sampling. By changing this number, user will change the subsets
of data sampled.</description>
</property>
<property>
<name>hive.io.exception.handlers</name>
<value></value>
<description>A list of io exception handler class names. This is used
to construct a list exception handlers to handle exceptions thrown
<description>String used as a prefix when auto generating column alias.
By default the prefix label will be appended with a column position number to form the column alias. Auto generation would happen if an aggregate function is used in a select clause without an explicit alias.</description>
<description>The class responsible logging client side performance metrics. Must be a subclass of org.apache.hadoop.hive.ql.log.PerfLogger</description>
</property>
<property>
<name>hive.start.cleanup.scratchdir</name>
<value>false</value>
<description>To cleanup the hive scratchdir while starting the hive server</description>
</property>
<property>
<name>hive.output.file.extension</name>
<value></value>
<description>String used as a file extension for output files. If not set, defaults to the codec extension for text files (e.g. ".gz"), or no extension otherwise.</description>
</property>
<property>
<name>hive.insert.into.multilevel.dirs</name>
<value>false</value>
<description>Where to insert into multilevel directories like
"insert directory '/HIVEFT25686/chinna/' from table"</description>
</property>
<property>
<name>hive.warehouse.subdir.inherit.perms</name>
<value>false</value>
<description>Set this to true if the the table directories should inherit the
permission of the warehouse or database directory instead of being created
with the permissions derived from dfs umask</description>
WARNING: org.apache.hadoop.metrics.jvm.EventCounter is deprecated. Please use org.apache.hadoop.log.metrics.EventCounter in all the log4j.properties files.
Logging initialized using configuration in jar:file:/home/hadoop/source/hive/lib/hive-common-0.10.0.jar!/hive-log4j.properties
Hive history file=/tmp/hadoop/hive_job_log_hadoop_201401012315_758621762.txt
hive> CREATE TABLE hbase_table_1(key int, value string)
> STORED BY 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
> WITH SERDEPROPERTIES ("hbase.columns.mapping" = ":key,cf1:val")
/2 
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