Query HIVE table in pyspark

Question

I am using CDH5.5

I have a table created in HIVE default database and able to query it from the HIVE command.

Output

hive> use default;  OK  Time taken: 0.582 seconds   hive> show tables;  OK  bank Time taken: 0.341 seconds, Fetched: 1 row(s)  hive> select count(*) from bank;  OK  542  Time taken: 64.961 seconds, Fetched: 1 row(s) 

However, I am unable to query the table from pyspark as it cannot recognize the table.

from pyspark.context import SparkContext  from pyspark.sql import HiveContext  sqlContext = HiveContext(sc)   sqlContext.sql("use default")  DataFrame[result: string]  sqlContext.sql("show tables").show()  +---------+-----------+  |tableName|isTemporary|  +---------+-----------+  +---------+-----------+   sqlContext.sql("FROM bank SELECT count(*)")  16/03/16 20:12:13 INFO parse.ParseDriver: Parsing command: FROM bank SELECT count(*) 16/03/16 20:12:13 INFO parse.ParseDriver: Parse Completed Traceback (most recent call last):     File "<stdin>", line 1, in <module>     File "/usr/lib/spark/python/pyspark/sql/context.py", line 552, in sql       return DataFrame(self._ssql_ctx.sql(sqlQuery), self)     File "/usr/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py",   line 538, in __call__     File "/usr/lib/spark/python/pyspark/sql/utils.py", line 40, in deco       raise AnalysisException(s.split(': ', 1)[1])   **pyspark.sql.utils.AnalysisException: no such table bank; line 1 pos 5** 

New Error

>>> from pyspark.sql import HiveContext >>> hive_context = HiveContext(sc) >>> bank = hive_context.table("default.bank") 16/03/22 18:33:30 INFO DataNucleus.Persistence: Property datanucleus.cache.level2 unknown - will be ignored 16/03/22 18:33:30 INFO DataNucleus.Persistence: Property hive.metastore.integral.jdo.pushdown unknown - will be ignored 16/03/22 18:33:44 INFO DataNucleus.Datastore: The class "org.apache.hadoop.hive.metastore.model.MFieldSchema" is tagged as "embedded-only" so does not have its own datastore table. 16/03/22 18:33:44 INFO DataNucleus.Datastore: The class "org.apache.hadoop.hive.metastore.model.MOrder" is tagged as "embedded-only" so does not have its own datastore table. 16/03/22 18:33:48 INFO DataNucleus.Datastore: The class "org.apache.hadoop.hive.metastore.model.MFieldSchema" is tagged as "embedded-only" so does not have its own datastore table. 16/03/22 18:33:48 INFO DataNucleus.Datastore: The class "org.apache.hadoop.hive.metastore.model.MOrder" is tagged as "embedded-only" so does not have its own datastore table. 16/03/22 18:33:50 INFO DataNucleus.Datastore: The class "org.apache.hadoop.hive.metastore.model.MResourceUri" is tagged as "embedded-only" so does not have its own datastore table. Traceback (most recent call last):   File "<stdin>", line 1, in <module>   File "/usr/lib/spark/python/pyspark/sql/context.py", line 565, in table     return DataFrame(self._ssql_ctx.table(tableName), self)   File "/usr/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py", line 538, in __call__   File "/usr/lib/spark/python/pyspark/sql/utils.py", line 36, in deco     return f(*a, **kw)   File "/usr/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line 300, in get_return_value py4j.protocol.Py4JJavaError: An error occurred while calling o22.table. : org.apache.spark.sql.catalyst.analysis.NoSuchTableException     at org.apache.spark.sql.hive.client.ClientInterface$$anonfun$getTable$1.apply(ClientInterface.scala:123)     at org.apache.spark.sql.hive.client.ClientInterface$$anonfun$getTable$1.apply(ClientInterface.scala:123)     at scala.Option.getOrElse(Option.scala:120)     at org.apache.spark.sql.hive.client.ClientInterface$class.getTable(ClientInterface.scala:123)     at org.apache.spark.sql.hive.client.ClientWrapper.getTable(ClientWrapper.scala:60)     at org.apache.spark.sql.hive.HiveMetastoreCatalog.lookupRelation(HiveMetastoreCatalog.scala:406)     at org.apache.spark.sql.hive.HiveContext$$anon$1.org$apache$spark$sql$catalyst$analysis$OverrideCatalog$$super$lookupRelation(HiveContext.scala:422)     at org.apache.spark.sql.catalyst.analysis.OverrideCatalog$$anonfun$lookupRelation$3.apply(Catalog.scala:203)     at org.apache.spark.sql.catalyst.analysis.OverrideCatalog$$anonfun$lookupRelation$3.apply(Catalog.scala:203)     at scala.Option.getOrElse(Option.scala:120)     at org.apache.spark.sql.catalyst.analysis.OverrideCatalog$class.lookupRelation(Catalog.scala:203)     at org.apache.spark.sql.hive.HiveContext$$anon$1.lookupRelation(HiveContext.scala:422)     at org.apache.spark.sql.SQLContext.table(SQLContext.scala:739)     at org.apache.spark.sql.SQLContext.table(SQLContext.scala:735)     at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)     at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)     at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)     at java.lang.reflect.Method.invoke(Method.java:606)     at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)     at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)     at py4j.Gateway.invoke(Gateway.java:259)     at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)     at py4j.commands.CallCommand.execute(CallCommand.java:79)     at py4j.GatewayConnection.run(GatewayConnection.java:207)     at java.lang.Thread.run(Thread.java:745) 

thanks

Answer 1

We cannot pass the Hive table name directly to Hive context sql method since it doesn't understand the Hive table name. One way to read Hive table in pyspark shell is:

from pyspark.sql import HiveContext hive_context = HiveContext(sc) bank = hive_context.table("default.bank") bank.show() 

To run the SQL on the hive table: First, we need to register the data frame we get from reading the hive table. Then we can run the SQL query.

bank.registerTempTable("bank_temp") hive_context.sql("select * from bank_temp").show()