How to read postgres DB tables through EMR jupyter lab notebook from amazon workspace

Question

I'm trying to read the table from postgres tables. but i'm facing below error. Note: i cannot be able to refer external files from local since it is a private workspace.

JDBC : Eg:

"url":"jdbc:postgresql://xxxx-xxxxx-postgresql-prod01.cluster-xxxx.xx-xx-1.rds.amazonaws.com:0000/db_xxx_txxx",

Error i'm getting like : "

java.lang.ClassNotFoundException: org.postgresql.Driver

"

An error was encountered:
An error occurred while calling o153.jdbc.
: java.lang.ClassNotFoundException: org.postgresql.Driver
    at java.net.URLClassLoader.findClass(URLClassLoader.java:387)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:418)
    at java.lang.ClassLoader.loadClass(ClassLoader.java:351)
    at org.apache.spark.sql.execution.datasources.jdbc.DriverRegistry$.register(DriverRegistry.scala:46)
    at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.$anonfun$driverClass$1(JDBCOptions.scala:102)
    at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.$anonfun$driverClass$1$adapted(JDBCOptions.scala:102)
    at scala.Option.foreach(Option.scala:407)
    at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.<init>(JDBCOptions.scala:102)
    at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.<init>(JDBCOptions.scala:38)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:32)
    at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:355)
    at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:325)
    at org.apache.spark.sql.DataFrameReader.$anonfun$load$3(DataFrameReader.scala:307)
    at scala.Option.getOrElse(Option.scala:189)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:307)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:225)
    at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:340)
    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 py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:282)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:238)
    at java.lang.Thread.run(Thread.java:750)

i've tried below code.

tables = read_table(
    url=URL,
    table="information_schema.tables",
    driver=DRIVER,
    user=USER,
    password=PASS
)

Answer 1

You need to add Postgres driver as a dependency/classpath first.

First copy the JAR onto the cluster or s3 and then in the first cell execute:

%%configure -f
{ "conf":{
          "spark.jars": "s3://JAR-LOCATION/postgresql.jar"
         }
}

Ref. Postgres JAR with EMR and Jupyter Notebooks

Alternatively, you can configure it while creating the SparkSession.

spark = SparkSession.builder.config('spark.driver.extraClassPath', '/JAR-LOCATION/postgresql.jar').getOrCreate()

Update: Based on your comment since you can't push JAR, you can use maven dependency

%%configure -f
{
    "conf": {"spark.jars.packages": "org.postgresql:postgresql:jar:42.4.3"}
}