When you run DROP TABLE on an external table, by default Hive drops only the metadata (schema). typeInfo (org.apache.hadoop.hive.ql.plan.ExprNodeGenericFuncDesc)) As mentioned in the differences, Hive temporary table have few limitation compared with regular tables. metadata of the external table. Example: CREATE TABLE IF NOT EXISTS hql.customer(cust_id INT, name STRING, created_date DATE) COMMENT 'A table … at org.apache.spark.sql.SQLContext$QueryExecution.toRdd(SQLContext.scala:933) If you also want to drop data along with partition fro external tables then you have to do it manually. Commons Attribution ShareAlike 4.0 License. at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$get_partitions_by_expr_result.read(ThriftHiveMetastore.java) **************************************************. stored on the file system, depicted in the diagram below. fine from hive shell. I had 3 partition and then issued hive drop partition command and it got succeeded. Created I have reproduced all the steps in both Zeppelin and spark-shell. table keeps its data outside the Hive metastore. Note: If PARTITIONED BY is String, it works fine . As of Hive 2.4.0 (HIVE-16324) the value of the property 'EXTERNAL' is parsed as a boolean (case insensitive true or false) instead of a case sensitive string comparison. Just performing an ALTER TABLE DROP PARTITION statement does remove the partition information from the metastore only. The RECOVER PARTITIONS clause automatically recognizes any … server_date=2016-10-13. FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask. Sorry about the logs, I was using two tables spark_2_test, spark_3_test. In addition, we can use the Alter table add partition command to add the new partitions for a table. when using Ranger, you need to be authorized by a policy, such as the default HDFS On the command-line of a node on your cluster, enter the following at org.apache.hadoop.hive.ql.parse.BaseSemanticAnalyzer.analyze(BaseSemanticAnalyzer.java:227) ====================== hive> ALTER TABLE sales drop if exists partition (year = 2020, quarter = 1), partition (year = 2020, quarter = 2); Here is how we dynamically pick partitions to drop. In contrast to the Hive managed table, an external table keeps its data outside the Hive metastore. at java.lang.reflect.Method.invoke(Method.java:497) at $iwC.(:41) at org.apache.spark.sql.hive.HiveContext.runSqlHive(HiveContext.scala:561) Hive Temporary Table Limitations. at org.apache.hadoop.hive.ql.parse.DDLSemanticAnalyzer.addTableDropPartsOutputs(DDLSemanticAnalyzer.java:3176) Hive does not manage, or restrict access, to the actual external data. Partitioning of table. at $line69.$eval$.(:7) Hive deals with two types of table structures like Internal and External tables depending on the loading and design of schema in Hive. It just removes these details from table metadata. ‎01-27-2017 If the table is external table then only the metadata is dropped. hiveCtx.sql("ALTER TABLE spark_4_test DROP IF EXISTS PARTITION (server_date ='2016-10-10')"). at $line69.$eval.$print() at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:138) thanks! table. at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$get_partitions_by_expr_result$get_partitions_by_expr_resultStandardScheme.read(ThriftHiveMetastore.java) In my case, it is date type. 4. You can learn more about Hive External Table here. at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.recv_get_partitions_by_expr(ThriftHiveMetastore.java:2277) Alternatively, Thanks for your reply. ====================== OK If don’t remember check here to know what is the equivalent value for each encoded character value, and use the actual value to drop it. Let say that there is a scenario in which you need to find the list of External Tables from all the Tables in a Hive Database using Spark. Hive doe not drop that data. This document lists some of the differences between the two but the fundamental difference is that Hive assumes that it ownsthe data for managed tables. Consequently, dropping of an external table does not affect the data. Serialization trace: at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180) at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857) at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:57) If the tables is an internal/managed table then the data along with metadata is removed permanently. To automatically detect new partition directories added through Hive or HDFS operations: In Impala 2.3 and higher, the RECOVER PARTITIONS clause scans a partitioned table to detect if any new partition directories were added outside of Impala, such as by Hive ALTER TABLE statements or by hdfs dfs or hadoop fs commands. There shouldn't be any issue with running DROP PARTITION from spark shell. External and internal tables. at (:43) at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) External table: EXTERNAL. You can also manually update or drop a Hive partition directly on HDFS using Hadoop commands, if you do so you need to run the MSCK command to synch up HDFS files with Hive Metastore. at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1059) The external table data is stored externally, while Hive metastore only contains the metadata schema. Created at $line69.$read$$iwC$$iwC.(:39) commands: Having authorization to HDFS through a Ranger policy, use the command To specify the location of an external table, you at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814) at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:725) External Tables have a two step process to alterr table drop partition + removing file ALTER TABLE table_name DROP [IF EXISTS] PARTITION partition_spec; hadoop fs -rm -r (:41) Refer to Differences between Hive External and Internal (Managed) Tables to understand the differences between managed and unmanaged tables in Hive.. Partitioning external tables works in the same way as in managed tables. Could you please accept the correct answer, so the question would be marked as answered? The hive partition is similar to table partitioning available in SQL server or any other RDBMS database tables. When we execute drop partition command on hive external 04:50 PM. In this tutorial, you will learn how to create, query, and drop an external table in Hive. END HIVE FAILURE OUTPUT On temporary tables, you cannot create partitions. How to create an external table? ... 77 more The default value of hive.exec.stagingdir which is a relative path, and also drop partition on a external table will not clear the real data. You May Also Like AlreadyExistsException(message:Table spark_3_test already exists).... ... dbName:default, tableName:spark_3_test, ...Partition not found (server_date = 2016-10-23). If you want the DROP TABLE command to also remove the actual data in the external table, as DROP TABLE does on a managed table, you need to configure the table properties accordingly. at $line69.$read$$iwC$$iwC$$iwC$$iwC.(:35) Another consequence is that data is at… You use an external table, which is a table that Hive does not manage, to import data from a file on a file system, into Hive. at org.apache.spark.sql.SQLContext$QueryExecution.toRdd(SQLContext.scala:933) This happened when we reproduce partition data onto a external table. at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:138) manage and store the actual data in the metastore. at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205) at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:57) Verify that the data now resides in the managed table also, drop the external The LOCATION clause in the CREATE TABLE specifies the location of external (not create external table tb_emp_ext (empno string, ename string, job string, managerno string, hiredate string, salary double, jiangjin double, deptno string ) row format delimited fields terminated by '\t'; at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.invoke(RetryingMetaStoreClient.java:156) 06:18 PM, The issue is addressed in 2.1.0 - https://issues.apache.org/jira/browse/SPARK-17388, Created at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147) at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.(:31) 02:36 PM. at org.apache.spark.repl.Main$.main(Main.scala:31) That is the caveat or feature (depending on your use case) of … When you drop a Hive table all the metadata information related to the table is dropped. at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.get_partitions_by_expr(ThriftHiveMetastore.java:2264) Verify that the external table schema definition is lost. for managed tables only. hive> show partitions spark_2_test; OK. server_date=2016-10-10. at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:657) at org.apache.spark.sql.hive.client.ClientWrapper$$anonfun$withHiveState$1.apply(ClientWrapper.scala:278) Below is an example of how to drop a temporary table. Verify that the Hive warehouse stores the student names in the external at $iwC$$iwC$$iwC$$iwC$$iwC.(:33) Next, you want Hive to at org.apache.spark.sql.hive.client.ClientWrapper.retryLocked(ClientWrapper.scala:233) OK ‎02-03-2017 Internal tables Internal Table is tightly coupled in nature.In this type of table, first we have to create table and load the data. When you drop an Internal table, it drops the table from Metastore, metadata and it’s data files from the data warehouse HDFS location. managed) table data. at java.lang.reflect.Method.invoke(Method.java:497) Try to give it clean shot - new table, new partitions, no locks of data/directories, no two tables with the same location, etc. Except this in the external table, when you delete a partition, the data file doesn't get deleted. hive> ALTER TABLE spark_2_test DROP PARTITION (server_date='2016-10-13'); 2 ALTER Table Drop Partition in Hive ALTER TABLE ADD PARTITION in Hive Alter table statement is used to change the table structure or properties of an existing table in Hive. at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840) Partition exists and drop partition command works fine in Hive shell. at org.apache.spark.sql.SQLContext$QueryExecution.toRdd$lzycompute(SQLContext.scala:933) scala> hiveCtx.sql("show partitions spark_2_test").collect().foreach(println); scala> hiveCtx.sql("ALTER TABLE spark_2_test DROP PARTITION (server_date='2016-10-10')"), 17/01/26 19:28:39 ERROR Driver: FAILED: SemanticException [Error 10006]: Partition not found (server_date = 2016-10-10) Let us create a table to manage “Wallet expenses”, which any digital wallet channel may have to track customers’ spend behavior, having the following columns: In order to track monthly expenses, we want to create a partitioned table with columns month and spender. at org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:69) at org.apache.hadoop.hive.ql.parse.DDLSemanticAnalyzer.analyzeAlterTableDropParts(DDLSemanticAnalyzer.java:2694) at $line69.$read$$iwC$$iwC$$iwC.(:37) external data. at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) Hive does not manage, or restrict access, to the actual at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.(:24) As a result, insert overwrite partition twice will happen to fail because of the target data to be moved has already existed.. Unlike management tables, external tables need to pass external Keyword to specify. When discover.partitions is enabled for a table, Hive performs an automatic refresh as follows: Adds corresponding partitions that are in the file system, but not in metastore, to the metastore. ‎02-03-2017 from a file on a file system, into Hive. at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:51) HDFS. table metadata, and verify that the data still resides in the managed table. loads data from. ‎01-29-2017 If you do though it violates invariants and expectations of Hive and you might see undefined behavior. hive> ALTER TABLE spark_2_test DROP PARTITION (server_date='2016-10-13'); Dropped the partition server_date=2016-10-13, ****************************************************. at org.apache.hadoop.hive.ql.parse.DDLSemanticAnalyzer.addTableDropPartsOutputs(DDLSemanticAnalyzer.java:3178) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:685) Hive has a Internal and External tables. at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) FAILED: SemanticException [Error 10006]: Partition not found (server_date = 2016-10-10) follows: After dropping an external table, the data is not gone. This chapter describes how to drop a table in Hive. at org.apache.spark.repl.Main.main(Main.scala) Partitions are used to divide the table into related parts. The issue is that the DROP TABLE statement doesn't seem to remove the data from HDFS. HIVE FAILURE OUTPUT at .(:47), Created We can try the below approach as well: Step1: Create 1 Internal Table and 2 External Table. at org.apache.spark.sql.DataFrame.(DataFrame.scala:129) Caused by: MetaException(message:Unable to find class: 㐀org.apache.hadoop.hive.ql.udf.generic.G ‎01-29-2017 at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945) The MSCK REPAIR TABLE command was designed to manually add partitions that are added to or removed from the file system, such as HDFS or S3, but are not present in the metastore. In contrast to the Hive managed table, an external at org.apache.spark.sql.hive.client.ClientWrapper.runSqlHive(ClientWrapper.scala:430) at org.apache.thrift.TServiceClient.receiveBase(TServiceClient.java:78) Hive warehouse. hive> alter table mytable drop partition (date='${hiveconf:INPUT_DATE}'); FAILED: SemanticException [Error 10006]: Partition not found (server_date = 2016-10-23) To retrieve it, you issue another CREATE EXTERNAL TABLE statement to load the data from the file system. Find answers, ask questions, and share your expertise. AlreadyExistsException(message:Partition already exists: Partition(values:[2016-10-10], dbName:default, tableName:spark_3_test, createTime:0, lastAccessTime:0, sd:StorageDescriptor(cols:[FieldSchema(name:name, type:string, comment:null), FieldSchema(name:dept, type:string, comment:null)], location:null, inputFormat:org.apache.hadoop.hive.ql.io.orc.OrcInputFormat, outputFormat:org.apache.hadoop.hive.ql.io.orc.OrcOutputFormat, compressed:false, numBuckets:2, serdeInfo:SerDeInfo(name:null, serializationLib:org.apache.hadoop.hive.ql.io.orc.OrcSerde, parameters:{serialization.format=1}), bucketCols:[dept], sortCols:[Order(col:dept, order:1)], parameters:{}, skewedInfo:SkewedInfo(skewedColNames:[], skewedColValues:[], skewedColValueLocationMaps:{}), storedAsSubDirectories:false), parameters:null)) The only difference is when you drop a partition on internal table the data gets dropped as well, but when you drop a partition on external table the data remains as is.
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