As mentioned in the differences, Hive temporary table have few limitation compared with regular tables. For an external table, If you are trying to drop a partition and as-well would like to delete the data. This page shows how to create, drop, and truncate Hive tables via Hive SQL (HQL). Unlike management tables, external tables need to pass external Keyword to specify. at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857) ‎02-03-2017 OK Spark - Drop partition command on hive external table fails, Re: Spark - Drop partition command on hive external table fails. OK at org.apache.spark.sql.hive.client.ClientWrapper.runSqlHive(ClientWrapper.scala:430) Below script drops all partitions from sales table with year greater than 2019. Create an external table schema definition that specifies the text format, at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180) at org.apache.thrift.TServiceClient.receiveBase(TServiceClient.java:78) FAILED: SemanticException [Error 10006]: Partition not found (server_date = 2016-10-10) at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819) at org.apache.spark.sql.DataFrame.(DataFrame.scala:144) Hive doe not drop that data. at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:138) create partition on hive external table You can create partition on Hive External table same as we did for Internal Tables. Verify that the data now resides in the managed table also, drop the external 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. persistence of table data on the files system after a. In this task, you create an external table from CSV (comma-separated values) data at org.apache.spark.sql.hive.client.ClientWrapper.withHiveState(ClientWrapper.scala:270) at org.apache.spark.sql.hive.client.ClientWrapper.withHiveState(ClientWrapper.scala:270) The LOCATION clause in the CREATE TABLE specifies the location of external (not metastore. OK 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. Not sure how it is related to the query you are running for "spark_2_test" table and for different partition. Verify that the external table schema definition is lost. ‎02-06-2017 for managed tables only. The primary purpose of defining an external table is to access and execute queries on data stored outside the Hive. at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:140) at org.apache.spark.sql.hive.client.ClientWrapper$$anonfun$runHive$1.apply(ClientWrapper.scala:440) at $line69.$read$$iwC$$iwC$$iwC.(:37) Partitions are used to divide the table into related parts. That is, all the data in the files still exists on the file system, it’s jut that Hive no longer knows that it’s there. Fundamentally, there are two types of tables in HIVE – Managed or Internal tables and external tables. The discover.partitions table property is automatically created and enabled for external partitioned tables. As a result, insert overwrite partition twice will happen to fail because of the target data to be moved has already existed.. at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:51) You can learn more about Hive External Table here. at org.apache.spark.sql.hive.client.ClientWrapper.runHive(ClientWrapper.scala:440) at org.apache.spark.sql.SQLContext$QueryExecution.toRdd$lzycompute(SQLContext.scala:933) at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:725) at java.lang.reflect.Method.invoke(Method.java:497) table keeps its data outside the Hive metastore. scala> hiveCtx.sql("show partitions spark_2_test").collect().foreach(println); scala> hiveCtx.sql("ALTER TABLE spark_2_test DROP PARTITION (server_date='2016-10-10')"), 17/01/26 19:28:39 ERROR Driver: FAILED: SemanticException [Error 10006]: Partition not found (server_date = 2016-10-10) Partitioning of table. The external table data is stored externally, while Hive metastore only contains the metadata schema. external data. at $line69.$read$$iwC$$iwC$$iwC$$iwC$$iwC.(:33) hive> show partitions spark_2_test; OK. server_date=2016-10-10. at org.apache.spark.sql.hive.client.ClientWrapper$$anonfun$runHive$1.apply(ClientWrapper.scala:455) at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:140) at org.apache.spark.sql.hive.client.ClientWrapper.runHive(ClientWrapper.scala:440) at java.lang.reflect.Method.invoke(Method.java:497) at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945) FAILED: SemanticException [Error 10006]: Partition not found (server_date = 2016-10-23) In a trace log above, in "HIVE FAILURE OUTPUT" section, you have: FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask. at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871) at org.apache.spark.sql.hive.client.ClientWrapper$$anonfun$runHive$1.apply(ClientWrapper.scala:451) Hive deals with two types of table structures like Internal and External tables depending on the loading and design of schema in Hive. CREATE EXTERNAL TABLE spark_4_test(name string, dept string ) PARTITIONED BY ( server_date date) LOCATION '/xxx/yyy/spark4', insert into table spark_4_test partition(server_date='2016-10-23') values ('a','d1'), insert into table spark_4_test partition(server_date='2016-10-10') values ('a','d1'). hadoop fs -rmr /maheshmogal.db/order_new/year=2019/month=7 at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) You can also manually update or drop a Hive partition directly on HDFS using Hadoop commands, if you do so you need to run the MSCK command to synch up HDFS files with Hive Metastore. The MSCK REPAIR TABLE command was designed to manually add partitions that are added to or removed from the file system, such as HDFS or S3, but are not present in the metastore. at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147) Hive default stores external table files also at Hive managed data warehouse location but recommends to use external location using LOCATION clause. at org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:69) END HIVE FAILURE OUTPUT at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.(:31) OK org.apache.hadoop.hive.ql.parse.SemanticException: Partition not found (server_date = 2016-10-10) Try to give it clean shot - new table, new partitions, no locks of data/directories, no two tables with the same location, etc. at $line69.$read.(:43) FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask. When you drop a Hive table all the metadata information related to the table is dropped. org.apache.spark.sql.execution.QueryExecutionException: FAILED: SemanticException [Error 10006]: Partition not found (server_date = 2016-10-10) ... 77 more 4. One way is to query hive metastore but this is always not possible as we may not have permission to access it. table from spark-shell we are getting below error.Same command works the schema. at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:997) at org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.invoke(RetryingMetaStoreClient.java:156) at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:657) 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. Hive Temporary Table Limitations. FAILED: SemanticException [Error 10006]: Partition not found (server_date = 2016-10-10) server_date=2016-10-13. We can try the below approach as well: Step1: Create 1 Internal Table and 2 External Table. table metadata, and verify that the data still resides in the managed table. OK table. Internal tables Internal Table is tightly coupled in nature.In this type of table, first we have to create table and load the data. ‎01-27-2017 ‎01-29-2017 Another consequence is that data is at… How to do it… Consequently, dropping of an external table does not affect the data. Hive does not manage, or restrict access, to the actual at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.listPartitionsByExpr(HiveMetaStoreClient.java:1130) Alternatively, OK at $line69.$read$$iwC.(:41) at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:685) On temporary tables, you cannot create partitions. at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.get_partitions_by_expr(ThriftHiveMetastore.java:2264) Dropping an external table just drops the metadata but not the actual data. at org.apache.spark.sql.hive.execution.HiveNativeCommand.run(HiveNativeCommand.scala:33) Hive metastore stores only the schema metadata of the external table. at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:57) at org.apache.spark.sql.hive.HiveContext.runSqlHive(HiveContext.scala:561) at org.apache.spark.sql.DataFrame.(DataFrame.scala:129) Just performing an ALTER TABLE DROP PARTITION statement does remove the partition information from the metastore only. In this task, you need access to HDFS to put a comma-separated values (CSV) file on Spark - Drop partition command on hive external ta... https://issues.apache.org/jira/browse/SPARK-17388, [ANNOUNCE] New Cloudera ODBC 2.6.12 Driver for Apache Impala Released, [ANNOUNCE] New Cloudera JDBC 2.6.20 Driver for Apache Impala Released, Transition to private repositories for CDH, HDP and HDF, [ANNOUNCE] New Applied ML Research from Cloudera Fast Forward: Few-Shot Text Classification, [ANNOUNCE] New JDBC 2.6.13 Driver for Apache Hive Released. ====================== at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065) Verify that the Hive warehouse stores the student names in the external You May Also Like at .(:47), Created at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135) 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.hadoop.hive.ql.Driver.runInternal(Driver.java:1170) I have reproduced all the steps in both Zeppelin and spark-shell. You use an external table, which is a table that Hive does not manage, to import data When we execute drop partition command on hive external at org.apache.spark.sql.hive.client.ClientWrapper.retryLocked(ClientWrapper.scala:233) This is usually caused by the table being an external table that doesn't allow Hive to perform all operations on it. Partition exists and drop partition command works fine in Hive shell. 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. at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) It fails. at $line69.$read$.() Created Create table. at org.apache.hadoop.hive.ql.parse.DDLSemanticAnalyzer.addTableDropPartsOutputs(DDLSemanticAnalyzer.java:3176) 2. at (:43) IMO it is related to the specific table configuration/definition. In this tutorial, you will learn how to create, query, and drop an external table in Hive. at $iwC$$iwC$$iwC.(:37) line or Ambari to create the directory and put the. This can be achieved as below. When you drop a table from Hive Metastore, it removes the table/column data and their metadata. at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:57) 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 (:39) 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)) In my case, it is date type. 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. HIVE FAILURE OUTPUT at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059) In contrast to the Hive managed table, an external table keeps its data outside the Hive metastore. TBLPROPERTIES ("external.table.purge"="true") in release 4.0.0+ (HIVE-19981) when … Alter external table as internal table -- … Partition exists and drop partition command works fine in Hive shell. Next, you want Hive to at org.apache.spark.sql.hive.client.ClientWrapper$$anonfun$withHiveState$1.apply(ClientWrapper.scala:278) Sorry about the logs, I was using two tables spark_2_test, spark_3_test. at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$get_partitions_by_expr_result.read(ThriftHiveMetastore.java) at org.apache.spark.sql.SQLContext$QueryExecution.toRdd(SQLContext.scala:933) fine from hive shell. SET hive.support.sql11.reserved.keywords=false 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. FAILED: SemanticException [Error 10006]: Partition not found (server_date = 2016-10-10) server_date=2016-10-11. How to create an external table? at org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:69) 06:38 PM. There shouldn't be any issue with running DROP PARTITION from spark shell. at org.apache.hadoop.hive.ql.metadata.Hive.getPartitionsByExpr(Hive.java:2289) Created 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. ‎02-01-2017 Caused by: MetaException(message:Unable to find class: 㐀org.apache.hadoop.hive.ql.udf.generic.G @subacini balakrishnan, I'm glad it worked for you. I had 3 partition and then issued hive drop partition command and it got succeeded. at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:138) I had 3 partition and then issued hive drop partition command and it got succeeded. before you drop the table, change its property to be EXTERNAL=FALSE). at org.apache.spark.sql.hive.HiveContext.runSqlHive(HiveContext.scala:561) 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. That means that the data, its properties and data layout will and can only be changed via Hive command. ====================== FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask. hiveCtx.sql("ALTER TABLE spark_4_test DROP IF EXISTS PARTITION (server_date ='2016-10-10')"). at org.apache.spark.sql.hive.client.ClientWrapper.retryLocked(ClientWrapper.scala:233) at org.apache.hadoop.hive.ql.parse.DDLSemanticAnalyzer.analyzeInternal(DDLSemanticAnalyzer.java:278) at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:57) at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945) AlreadyExistsException(message:Table spark_3_test already exists).... ... dbName:default, tableName:spark_3_test, ...Partition not found (server_date = 2016-10-23). at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1059) at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.(:24) at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.recv_get_partitions_by_expr(ThriftHiveMetastore.java:2277) at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:120) OK A major difference between an external and a managed (internal) table: the You create a managed table. Except this in the external table, when you delete a partition, the data file doesn't get deleted. ‎01-29-2017 The issue is that the DROP TABLE statement doesn't seem to remove the data from HDFS. 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. 06:18 PM, The issue is addressed in 2.1.0 - https://issues.apache.org/jira/browse/SPARK-17388, Created at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:57) Hive metastore stores only the schema at $line69.$read$$iwC$$iwC$$iwC$$iwC.(:35) need to include the specification in the table creation statement as at org.apache.spark.sql.hive.execution.HiveNativeCommand.run(HiveNativeCommand.scala:33) Created at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:665) The RECOVER PARTITIONS clause automatically recognizes any … at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$loop(SparkILoop.scala:670) at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.(:29) In contrast to the Hive managed table, an external ====================== ====================== To create an External table you need to use EXTERNAL clause. thanks! Hi, Commons Attribution ShareAlike 4.0 License. OK at org.apache.spark.sql.SQLContext$QueryExecution.toRdd$lzycompute(SQLContext.scala:933) at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945) Create the schema for the managed table to store the data in Hive CREATE TABLE expenses (Month String, Spender String, Merchant String, Mode String, Amount Float ) PARTITIONED BY (Month STRING, Spender STRING) Row format delimited fields terminated by ","; We get to know the partition keys usin… follows: After dropping an external table, the data is not gone. hiveCtx.sql(s"ALTER TABLE spark_2_test DROP IF EXISTS PARTITION (server_date='2016-10-10')"); Created 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. at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205) at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:138) at $line69.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.(:24) at $line69.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.(:31) AlreadyExistsException(message:Table spark_3_test already exists) 04:20 PM. Find answers, ask questions, and share your expertise. FAILED: SemanticException [Error 10006]: Partition not found (server_date = 2016-10-23) 03:53 PM. Hive warehouse. at org.apache.spark.sql.DataFrame.(DataFrame.scala:129) The default value of hive.exec.stagingdir which is a relative path, and also drop partition on a external table will not clear the real data. managed) table data. This chapter describes how to drop a table in Hive. at $line69.$eval$.() DATABASE LOCATION '' works To specify the location of an external table, you metadata of the external table. OK at $line69.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.(:29) Created Another thing you can try is what's suggested in this thread (i.e. Partitions make data querying more efficient. at $line69.$eval$.(:7) The hive partition is similar to table partitioning available in SQL server or any other RDBMS database tables. at com.sun.proxy.$Proxy44.listPartitionsByExpr(Unknown Source) at org.apache.spark.sql.DataFrame.(DataFrame.scala:144) If you do not use Ranger and an ACL is not in place that allows you to access loads data from. hive> alter table mytable drop partition (date='${hiveconf:INPUT_DATE}'); For example, substitute the URI of your HiveServer: The results from the managed table Names appears. all-path policy (shown below) to access HDFS. at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) It just removes these details from table metadata. manage and store the actual data in the metastore. at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:725) at org.apache.spark.sql.hive.client.ClientWrapper$$anonfun$runHive$1.apply(ClientWrapper.scala:440) When you drop an Internal table, it drops the table from Metastore, metadata and it’s data files from the data warehouse HDFS location. HDFS, you need to log in to a node on your cluster as the hdfs user. at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814) 06:44 PM, Seems you are providing a different log as it is showing some different error for various partition as partition not found, Partition not found (server_date = 2016-10-10) OK OK OK FAILED: SemanticException [Error 10006]: Partition not found (server_date = 2016-10-23) OK FAILED: SemanticException [Error 10006]: Partition not found (server_date = 2016-10-23) OK FAILED: SemanticException [Error 10006]: Partition not found (server_date = 2016-10-10). To retrieve it, you issue another CREATE EXTERNAL TABLE statement to load the data from the file system. From spark-shell, execute drop partition command. at $iwC.(:41) at $iwC$$iwC$$iwC$$iwC$$iwC.(:33) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) Here we go! Below is an example of how to drop a temporary table. This task demonstrates the following Hive principles: Specifying a database location in the CREATE DATABASE command, for example CREATE 17/01/26 19:28:39 ERROR ClientWrapper: Date is not supported as type for partitions. from a file on a file system, into Hive. Hive stores tables in partitions. at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) The actual data is still accessible outside of Hive. You know the actual partition when you created. Move the external table data to the managed table. An external table is a table that describes the schema or metadata of external files. at org.apache.hadoop.hive.ql.Driver.compile(Driver.java:308) at org.apache.spark.sql.hive.client.ClientWrapper.runSqlHive(ClientWrapper.scala:430) at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1049) This happened when we reproduce partition data onto a external table. Hive has a Internal and External tables. Partitioning external tables works in the same way as in managed tables. The data still lives in a normal file system and nothing is stopping you from changing it without telling Hive about it. at $line69.$read$.(:47) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at org.apache.spark.sql.SQLContext$QueryExecution.toRdd(SQLContext.scala:933) Managed table drop: Hive deletes the data and the metadata stored in the at org.apache.hadoop.hive.ql.parse.DDLSemanticAnalyzer.addTableDropPartsOutputs(DDLSemanticAnalyzer.java:3178) stored on the file system, depicted in the diagram below. at org.apache.hadoop.hive.ql.Driver.compile(Driver.java:424) Thanks for your reply. 03:09 PM, Created at org.apache.spark.repl.Main.main(Main.scala) at $iwC$$iwC$$iwC$$iwC.(:35) On the command-line of a node on your cluster, enter the following 2)Create table and overwrite with required partitioned data hive> CREATE TABLE `emptable_tmp`( 'rowid` string,PARTITIONED BY (`od` string) ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe' STORED AS INPUTFORMAT 'org.apache.hadoop.mapred.SequenceFileInputFormat'; hive> insert into emptable_tmp partition(od) … In addition, we can use the Alter table add partition command to add the new partitions for a table. at org.apache.hadoop.hive.ql.parse.DDLSemanticAnalyzer.analyzeAlterTableDropParts(DDLSemanticAnalyzer.java:2694) That is the caveat or feature (depending on your use case) of … Example: CREATE TABLE IF NOT EXISTS hql.customer(cust_id INT, name STRING, created_date DATE) COMMENT 'A table … at $iwC$$iwC.(:39) at org.apache.spark.sql.hive.client.ClientWrapper$$anonfun$withHiveState$1.apply(ClientWrapper.scala:278) Note: If PARTITIONED BY is String, it works fine . hive> ALTER TABLE spark_2_test DROP PARTITION (server_date='2016-10-13'); Dropped the partition server_date=2016-10-13, ****************************************************. at java.lang.reflect.Method.invoke(Method.java:497) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) Just clean shot. If the table is external table then only the metadata is dropped. **************************************************. Refer to Differences between Hive External and Internal (Managed) Tables to understand the differences between managed and unmanaged tables in Hive.. at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1340) HDFS. at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) 04:50 PM. External table: EXTERNAL. Create an insert-only transactional table, Altering tables from flat to transactional, Create a materialized view and store it in Druid, Create and use a partitioned materialized view, Query a SQL data source using the JdbcStorageHandler, Creative When you run DROP TABLE on an external table, by default Hive drops only the metadata (schema). In both tables i am getting same error. If you also want to drop data along with partition fro external tables then you have to do it manually. Dropping an External table drops just the table from Metastore and the actual data in HDFS will not be removed. hive> ALTER TABLE spark_2_test DROP PARTITION (server_date='2016-10-13'); For example in the above weather table the data can be partitioned on the basis of year and month and when query is fired on weather table this partition can be used as one of the column. commands: Having authorization to HDFS through a Ranger policy, use the command at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147) 02:36 PM. at org.apache.hadoop.hive.ql.parse.BaseSemanticAnalyzer.analyze(BaseSemanticAnalyzer.java:227) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at org.apache.hadoop.hive.ql.Driver.compileInternal(Driver.java:1122) at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902) Hive does not manage, or restrict access, to the actual external data. If the tables is an internal/managed table then the data along with metadata is removed permanently. at org.apache.spark.repl.Main$.main(Main.scala:31) Serialization trace: DROP TABLE IF NOT EXISTS emp.employee_temp 5. 1. Hive partition is a way to organize a large table into several smaller tables based on one or multiple columns (partition key, for example, date, state e.t.c). Hive ALTER TABLE command is used to update or drop a partition from a Hive Metastore and HDFS location (managed table). It can be a normal table (stored in Metastore) or an external table (stored in local file system); Hive treats both in … at $line69.$eval.$print() ‎02-03-2017 Hive Drop Temporary Table. at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:138) Execute same from spark shell (throws "partition not found" error even though it is present). Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type. typeInfo (org.apache.hadoop.hive.ql.plan.ExprNodeGenericFuncDesc)) Please change partition key type to string. at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$get_partitions_by_expr_result$get_partitions_by_expr_resultStandardScheme.read(ThriftHiveMetastore.java) This task assumes you created a partitioned external table named emp_part that stores partitions … To automatically detect new partition directories added through Hive or HDFS operations: In Impala 2.3 and higher, the RECOVER PARTITIONS clause scans a partitioned table to detect if any new partition directories were added outside of Impala, such as by Hive ALTER TABLE statements or by hdfs dfs or hadoop fs commands. at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:51) External and internal tables. at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) External table drop: Hive drops only the metadata, consisting mainly of at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$get_partitions_by_expr_result$get_partitions_by_expr_resultStandardScheme.read(ThriftHiveMetastore.java)
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