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The "Hive/Tutorial" page has been changed by Ning Zhang. http://wiki.apache.org/hadoop/Hive/Tutorial?action=diff&rev1=32&rev2=33 -------------------------------------------------- * When there are already non-empty partitions exists for the dynamic partition columns, (e.g., country='CA' exists under some ds root partition), it will be overwritten if the dynamic partition insert saw the same value (say 'CA') in the input data. This is in line with the 'insert overwrite' semantics. However, if the partition value 'CA' does not appear in the input data, the existing partition will not be overwritten. * Since a Hive partition corresponds to a directory in HDFS, the partition value has to conform to the HDFS path format (URI in Java). Any character having a special meaning in URI (e.g., '%', ':', '/', '#') will be escaped with '%' followed by 2 bytes of its ASCII value. * If the input column is a type different than STRING, its value will be first converted to STRING to be used to construct the HDFS path. - * If the input column value is NULL or empty string, the row will be put into a special partition, whose name is controlled by the hive parameter hive.exec.default.dynamic.partition.name. The default value is __HIVE_DEFAULT_PARTITION__. Basically this partition will contain all "bad" rows whose value are not valid partition names. The caveat of this approach is that the bad value will be lost and is replaced by __HIVE_DEFAULT_PARTITION__ if you select them Hive. JIRA HIVE-1309 is a solution to let user specify "bad file" to retain the input partition column values as well. + * If the input column value is NULL or empty string, the row will be put into a special partition, whose name is controlled by the hive parameter hive.exec.default.dynamic.partition.name. The default value is `__HIVE_DEFAULT_PARTITION__`. Basically this partition will contain all "bad" rows whose value are not valid partition names. The caveat of this approach is that the bad value will be lost and is replaced by `__HIVE_DEFAULT_PARTITION__` if you select them Hive. JIRA HIVE-1309 is a solution to let user specify "bad file" to retain the input partition column values as well. - * Dynamic partition insert could potentially resource hog in that it could generate a large number of partitions in a short time. To get yourself buckled, we define two parameters hive.exec.max.dynamic.partitions (default value being 1000) which is the total number of dynamic partitions could be created by one DML and hive.exec.max.dynamic.partitions.pernode (default value being 100) which is the maximum dynamic partitions that can be created for each mapper or reducer. If one mapper or reducer created more than that the threshold, a fatal error will be raised from the mapper/reducer (through counter) and the whole job will be killed. If each mapper/reducer did not exceed the limit but the total number of dynamic partitions does, then an exception is raised at the end of the job before the intermediate data are moved to the final destination. + * Dynamic partition insert could potentially resource hog in that it could generate a large number of partitions in a short time. To get yourself buckled, we define three parameters: + * '''hive.exec.max.dynamic.partitions.pernode''' (default value being 100) is the maximum dynamic partitions that can be created by each mapper or reducer. If one mapper or reducer created more than that the threshold, a fatal error will be raised from the mapper/reducer (through counter) and the whole job will be killed. + * '''hive.exec.max.dynamic.partitions''' (default value being 1000) is the total number of dynamic partitions could be created by one DML. If each mapper/reducer did not exceed the limit but the total number of dynamic partitions does, then an exception is raised at the end of the job before the intermediate data are moved to the final destination. + * '''hive.max.created.files''' (default value being 100000) is the maximum total number of files created by all mappers and reducers. This is implemented by updating a Hadoop counter by each mapper/reducer whenever a new file is created. If the total number is exceeding hive.max.created.files, a fatal error will be thrown and the job will be killed. + * Another situation we want to protect against dynamic partition insert is that the user may accidentally specify all partitions to be dynamic partitions without specifying one static partition, while the original intention is to just overwrite the sub-partitions of one root partition. We define another parameter hive.exec.dynamic.partition.mode=strict to prevent the all-dynamic partition case. In the strict mode, you have to specify at least one static partition. The default mode is strict. In addition, we have a parameter hive.exec.dynamic.partition=true/false to control whether to allow dynamic partition at all. The default value is false. - * Currently dynamic partition insert will not work with hive.merge.mapfiles=true or hive.merge.mapredfiles=true, so it internally turns off the merge parameters. The reason is that if either of the merge parameters is set to true, there will be a map reduce job for that particular partition to merge all files into one. In dynamic partition insert, we do not know the number of partitions at compile time thus no MapReduce job could be generated. There is a new JIRA HIVE-1307 filed for this task. + * In Hive 0.6, dynamic partition insert does not work with hive.merge.mapfiles=true or hive.merge.mapredfiles=true, so it internally turns off the merge parameters. Merging files in dynamic partition inserts are supported in Hive 0.7 (see JIRA HIVE-1307 for details). Troubleshooting and best practices: * As stated above, there are too many dynamic partitions created by a particular mapper/reducer, a fatal error could be raised and the job will be killed. The error message looks something like: {{{
