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Je cours une requête de ruche qui sélectionne des données d'une table et insère le résultat dans une autre table partitionnée de ruche en utilisant spark-sql. En l'insérant, il faut 1536 partitions. Mais l'étincelle ne parvient pas à insérer des données avec 1536 partitions I augmenté partitions eventhough max à 2000.Impossible d'augmenter les partitions dynamiques hive dans spark en utilisant spark-sql
Ci-dessous commande:
étincelle sql --num-exécuteurs de fil --master 14 --executor- mémoire 45G --executor-cores 30 --driver-memory 10G --conf spark.dynamicAllocation.enabled = false -e "SET hive.exec.dynamic.partition = true; SET hive.exec.dynamic.partition. mode = nonstrict; SET hive.exec.max.dynamic.partitions = 2000; insérer dans le tableau weatherdata_part_rv.weather_data_daily_model_location_mapping_rv partition (mod el_id, record_date) sélectionner y.rec_id, x.municipal_id, x.model_id, y.record_date de (select * from weatherdata_part_rv.model_location_xref) x jointure externe gauche weatherdata_part_rv.weather_data_daily y sur x.municipal_id = y.weather_station_id; "
pile d'erreur:
spark-sql --master yarn --num-executors 14 --executor-memory 45G --executor-cores 30 --driver-memory 10G --conf spark.dynamicAllocation.enabled=false -e "SET hive.exec.dynamic.partition = true;SET hive.exec.dynamic.partition.mode = nonstrict;SET hive.exec.max.dynamic.partitions = 2000;
> insert into table weatherdata_part_rv.weather_data_daily_model_location_mapping_rv partition (model_id,record_date) select y.rec_id,x.municipal_id,y.temprature_min_in_celcius,y.temprature_max_in_celcius,y.rainfall_in_mm,y.relative_humidity_min,y.relative_humidity_max,y.radiation_max,y.wind_intensity,y.wind_direction,y.cloud_coverage,y.soil_temprature_in_celcius,y.water_quantity_in_soil,y.lmdt,y.icon,y.probablity_of_rainfall,y.rain_acc_20feb_onwards,x.model_id,y.record_date from (select * from weatherdata_part_rv.model_location_xref) x left outer join weatherdata_part_rv.weather_data_daily y on x.municipal_id=y.weather_station_id;"
17/05/12 09:44:05 WARN ObjectStore: Version information not found in metastore. hive.metastore.schema.verification is not enabled so recording the schema version 1.2.0
17/05/12 09:44:05 WARN ObjectStore: Failed to get database default, returning NoSuchObjectException
17/05/12 09:44:08 WARN Client: Neither spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading libraries under SPARK_HOME.
hive.exec.dynamic.partition true
Time taken: 1.874 seconds, Fetched 1 row(s)
hive.exec.dynamic.partition.mode nonstrict
Time taken: 0.67 seconds, Fetched 1 row(s)
hive.exec.max.dynamic.partitions 2000
Time taken: 0.047 seconds, Fetched 1 row(s)
17/05/12 09:58:30 ERROR SparkSQLDriver: Failed in [
insert into table weatherdata_part_rv.weather_data_daily_model_location_mapping_rv partition (model_id,record_date) select y.rec_id,x.municipal_id,y.temprature_min_in_celcius,y.temprature_max_in_celcius,y.rainfall_in_mm,y.relative_humidity_min,y.relative_humidity_max,y.radiation_max,y.wind_intensity,y.wind_direction,y.cloud_coverage,y.soil_temprature_in_celcius,y.water_quantity_in_soil,y.lmdt,y.icon,y.probablity_of_rainfall,y.rain_acc_20feb_onwards,x.model_id,y.record_date from (select * from weatherdata_part_rv.model_location_xref) x left outer join weatherdata_part_rv.weather_data_daily y on x.municipal_id=y.weather_station_id]
java.lang.reflect.InvocationTargetException
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.sql.hive.client.Shim_v1_2.loadDynamicPartitions(HiveShim.scala:823)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$loadDynamicPartitions$1.apply$mcV$sp(HiveClientImpl.scala:689)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$loadDynamicPartitions$1.apply(HiveClientImpl.scala:687)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$loadDynamicPartitions$1.apply(HiveClientImpl.scala:687)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:283)
at org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:230)
at org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:229)
at org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:272)
at org.apache.spark.sql.hive.client.HiveClientImpl.loadDynamicPartitions(HiveClientImpl.scala:687)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$loadDynamicPartitions$1.apply$mcV$sp(HiveExternalCatalog.scala:796)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$loadDynamicPartitions$1.apply(HiveExternalCatalog.scala:784)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$loadDynamicPartitions$1.apply(HiveExternalCatalog.scala:784)
at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:95)
at org.apache.spark.sql.hive.HiveExternalCatalog.loadDynamicPartitions(HiveExternalCatalog.scala:784)
at org.apache.spark.sql.hive.execution.InsertIntoHiveTable.sideEffectResult$lzycompute(InsertIntoHiveTable.scala:268)
at org.apache.spark.sql.hive.execution.InsertIntoHiveTable.sideEffectResult(InsertIntoHiveTable.scala:170)
at org.apache.spark.sql.hive.execution.InsertIntoHiveTable.doExecute(InsertIntoHiveTable.scala:347)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:114)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:114)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:135)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:132)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:113)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:87)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:87)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:185)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64)
at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:592)
at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:699)
at org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.run(SparkSQLDriver.scala:62)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:335)
at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:376)
at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:311)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.main(SparkSQLCLIDriver.scala:168)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.main(SparkSQLCLIDriver.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:738)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: Number of dynamic partitions created is 1536, which is more than 1000. To solve this try to set hive.exec.max.dynamic.partitions to at least 1536.
at org.apache.hadoop.hive.ql.metadata.Hive.loadDynamicPartitions(Hive.java:1578)
... 48 more
java.lang.reflect.InvocationTargetException
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.sql.hive.client.Shim_v1_2.loadDynamicPartitions(HiveShim.scala:823)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$loadDynamicPartitions$1.apply$mcV$sp(HiveClientImpl.scala:689)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$loadDynamicPartitions$1.apply(HiveClientImpl.scala:687)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$loadDynamicPartitions$1.apply(HiveClientImpl.scala:687)
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:283)
at org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:230)
at org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:229)
at org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:272)
at org.apache.spark.sql.hive.client.HiveClientImpl.loadDynamicPartitions(HiveClientImpl.scala:687)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$loadDynamicPartitions$1.apply$mcV$sp(HiveExternalCatalog.scala:796)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$loadDynamicPartitions$1.apply(HiveExternalCatalog.scala:784)
at org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$loadDynamicPartitions$1.apply(HiveExternalCatalog.scala:784)
at org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:95)
at org.apache.spark.sql.hive.HiveExternalCatalog.loadDynamicPartitions(HiveExternalCatalog.scala:784)
at org.apache.spark.sql.hive.execution.InsertIntoHiveTable.sideEffectResult$lzycompute(InsertIntoHiveTable.scala:268)
at org.apache.spark.sql.hive.execution.InsertIntoHiveTable.sideEffectResult(InsertIntoHiveTable.scala:170)
at org.apache.spark.sql.hive.execution.InsertIntoHiveTable.doExecute(InsertIntoHiveTable.scala:347)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:114)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:114)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:135)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:132)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:113)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:87)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:87)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:185)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64)
at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:592)
at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:699)
at org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.run(SparkSQLDriver.scala:62)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:335)
at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:376)
at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:311)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.main(SparkSQLCLIDriver.scala:168)
at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.main(SparkSQLCLIDriver.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:738)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: Number of dynamic partitions created is 1536, which is more than 1000. To solve this try to set hive.exec.max.dynamic.partitions to at least 1536.
at org.apache.hadoop.hive.ql.metadata.Hive.loadDynamicPartitions(Hive.java:1578)
... 48 more
est-il une limite dans les partitions de la ruche maximum dans étincelle?
Si oui, y a-t-il un moyen d'augmenter le nombre maximum de partitions?
Depuis Spark 2.0.0, vous ne pouvez pas configurer hiveclient dynnamically en utilisant l'opérateur SET. https://issues.apache.org/jira/browse/SPARK-19881 –
Oui. C'est dû à la dernière version d'étincelle. Cela a fonctionné quand j'ai ajouté la propriété dans le fichier hive-site.xml. Merci –