unable to give schema name as input while creating dataframe from hive table in scala

Question

I am trying to create a dataframe from an existing hive table present in clickstream_db schema.

val ganulardataframe=hc.table("clickstream_db.granulartable");

it is giving an error :

org.apache.spark.sql.catalyst.analysis.NoSuchTableException
        at org.apache.spark.sql.hive.client.ClientInterface$$anonfun$getTable$1.apply(ClientInterface.scala:112)
        at org.apache.spark.sql.hive.client.ClientInterface$$anonfun$getTable$1.apply(ClientInterface.scala:112)
        at scala.Option.getOrElse(Option.scala:120)
        at org.apache.spark.sql.hive.client.ClientInterface$class.getTable(ClientInterface.scala:112)
        at org.apache.spark.sql.hive.client.ClientWrapper.getTable(ClientWrapper.scala:61)
        at org.apache.spark.sql.hive.HiveMetastoreCatalog.lookupRelation(HiveMetastoreCatalog.scala:227)
        at org.apache.spark.sql.hive.HiveContext$$anon$2.org$apache$spark$sql$catalyst$analysis$OverrideCatalog$$super$lookupRelation(HiveContext.scala:373)
        at org.apache.spark.sql.catalyst.analysis.OverrideCatalog$$anonfun$lookupRelation$3.apply(Catalog.scala:165)
        at org.apache.spark.sql.catalyst.analysis.OverrideCatalog$$anonfun$lookupRelation$3.apply(Catalog.scala:165)
        at scala.Option.getOrElse(Option.scala:120)
        at org.apache.spark.sql.catalyst.analysis.OverrideCatalog$class.lookupRelation(Catalog.scala:165)
        at org.apache.spark.sql.hive.HiveContext$$anon$2.lookupRelation(HiveContext.scala:373)
        at org.apache.spark.sql.SQLContext.table(SQLContext.scala:765)
        at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:23)
        at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:28)
        at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:30)
        at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:32)
        at $iwC$$iwC$$iwC$$iwC.<init>(<console>:34)
        at $iwC$$iwC$$iwC.<init>(<console>:36)
        at $iwC$$iwC.<init>(<console>:38)
        at $iwC.<init>(<console>:40)
        at <init>(<console>:42)
        at .<init>(<console>:46)
        at .<clinit>(<console>)
        at .<init>(<console>:7)
        at .<clinit>(<console>)
        at $print(<console>)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
        at java.lang.reflect.Method.invoke(Method.java:497)
        at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
        at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1338)
        at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
        at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
        at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
        at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
        at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
        at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
        at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:657)
        at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:665)
        at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$loop(SparkILoop.scala:670)
        at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:997)
        at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
        at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
        at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
        at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
        at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
        at org.apache.spark.repl.Main$.main(Main.scala:31)
        at org.apache.spark.repl.Main.main(Main.scala)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
        at java.lang.reflect.Method.invoke(Method.java:497)
        at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:665)
        at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:170)
        at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:193)
        at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:112)
        at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

If I give granulartable as input it is looking for this table in default schema.

val ganulardataframe=hc.table("granulartable");

one solution I can think of is creating the same table in default db and creating the dataframe from it.

Is there a way to give schema name to the "table" function?

Thank you.

Answer 1

Try this, it should work

val l=hc.sql("select * from clickstream_db.granulartable");

Instead of table use sql and get the data using sql query .

Answer 2

hc.sql("use clickstream_db");

By default hive will use default data base. we should change it to specific data base that you want to use.

val ganulardataframe=hc.table("granulartable");