postgresql - Apache Spark : JDBC connection not working

Question

I have asked this question previously also but did not got any answer (Not able to connect to postgres using jdbc in pyspark shell).

I have successfully installed Spark 1.3.0 on my local windows and ran sample programs to test using pyspark shell.

Now, I want to run Correlations from Mllib on the data that is stored in Postgresql, but I am not able to connect to postgresql.

I have successfully added the required jar (tested this jar) in the classpath by running

pyspark --jars "C:pathojarpostgresql-9.2-1002.jdbc3.jar"

I can see that jar is successfully added in environment UI.

When I run the following in pyspark shell-

from pyspark.sql import SQLContext
sqlContext = SQLContext(sc)
df = sqlContext.load(source="jdbc",url="jdbc:postgresql://[host]/[dbname]", dbtable="[schema.table]")  

I get this ERROR -

>>> df = sqlContext.load(source="jdbc",url="jdbc:postgresql://[host]/[dbname]", dbtable="[schema.table]")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:UsersACERNEW3DesktopSparkspark-1.3.0-bin-hadoop2.4pythonpysparksqlcontext.py", line 482, in load
    df = self._ssql_ctx.load(source, joptions)
  File "C:UsersACERNEW3DesktopSparkspark-1.3.0-bin-hadoop2.4pythonlibpy4j-0.8.2.1-src.zippy4jjava_gateway.py", line 538, in __call__
  File "C:UsersACERNEW3DesktopSparkspark-1.3.0-bin-hadoop2.4pythonlibpy4j-0.8.2.1-src.zippy4jprotocol.py", line 300, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o20.load.
: java.sql.SQLException: No suitable driver found for     jdbc:postgresql://[host]/[dbname]
        at java.sql.DriverManager.getConnection(DriverManager.java:602)
        at java.sql.DriverManager.getConnection(DriverManager.java:207)
        at org.apache.spark.sql.jdbc.JDBCRDD$.resolveTable(JDBCRDD.scala:94)
        at org.apache.spark.sql.jdbc.JDBCRelation.<init>    (JDBCRelation.scala:125)
        at  org.apache.spark.sql.jdbc.DefaultSource.createRelation(JDBCRelation.scala:114)
        at org.apache.spark.sql.sources.ResolvedDataSource$.apply(ddl.scala:290)
        at org.apache.spark.sql.SQLContext.load(SQLContext.scala:679)
        at org.apache.spark.sql.SQLContext.load(SQLContext.scala:667)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
        at java.lang.reflect.Method.invoke(Method.java:597)
        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:619)

Answer 1

I had this exact problem with mysql/mariadb, and got BIG clue from this question

So your pyspark command should be:

pyspark --conf spark.executor.extraClassPath=<jdbc.jar> --driver-class-path <jdbc.jar> --jars <jdbc.jar> --master <master-URL>

Also watch for errors when pyspark start like "Warning: Local jar ... does not exist, skipping." and "ERROR SparkContext: Jar not found at ...", these probably mean you spelled the path wrong.