I want to use Spark to process some data from a JDBC source. But to begin with, instead of reading original tables from JDBC, I want to run some queries on the JDBC side to filter columns and join tables, and load the query result as a table in Spark SQL.
The following syntax to load raw JDBC table works for me:
df_table1 = sqlContext.read.format('jdbc').options(
url="jdbc:mysql://foo.com:3306",
dbtable="mydb.table1",
user="me",
password="******",
driver="com.mysql.jdbc.Driver" # mysql JDBC driver 5.1.41
).load()
df_table1.show() # succeeded
According to Spark documentation (I'm using PySpark 1.6.3):
dbtable: The 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.
So just for experiment, I tried something simple like this:
df_table1 = sqlContext.read.format('jdbc').options(
url="jdbc:mysql://foo.com:3306",
dbtable="(SELECT * FROM mydb.table1) AS table1",
user="me",
password="******",
driver="com.mysql.jdbc.Driver"
).load() # failed
It threw the following exception:
com.mysql.jdbc.exceptions.jdbc4.MySQLSyntaxErrorException: You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near 'table1 WHERE 1=0' at line 1
I also tried a few other variations of the syntax (add / remove parentheses, remove 'as' clause, switch case, etc) without any luck. So what would be the correct syntax? Where can I find more detailed documentation for the syntax? Besides, where does this weird "WHERE 1=0" in error message come from? Thanks!
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