Hi all,
According to the official document, SparkContext can load datatable to
dataframe using the DataSources API. However, it just supports the following
properties:Property NameMeaningurlThe JDBC URL to connect to.dbtableThe JDBC
table that should be read. Note that anything that is valid in a `FROM` clause
of a SQL query can be used. For example, instead of a full table you could also
use a subquery in parentheses.driverThe class name of the JDBC driver needed to
connect to this URL. This class with be loaded on the master and workers before
running an JDBC commands to allow the driver to register itself with the JDBC
subsystem.partitionColumn, lowerBound, upperBound, numPartitionsThese options
must all be specified if any of them is specified. They describe how to
partition the table when reading in parallel from multiple workers.
partitionColumn must be a numeric column from the table in question.It lets me
confused how to pass the username, password or other info? BTW, I am connecting
to Postgresql like this: val dataFrame = sqlContext.load("jdbc", Map(
"url" -> "jdbc:postgresql://192.168.1.110:5432/demo", //how to pass username
and password? "driver" -> "org.postgresql.Driver", "dbtable" ->
"schema.tab_users" ))
Thanks.
RegardsYi
