How Can I Fetch Specific Query Results from an External Database Using PySpark's JDBC?

Fetching Specific Query Results from External Database in Apache Spark 2.0.0

When working with external databases in Apache Spark 2.0.0 using PySpark, users may want to fetch data from specific queries rather than grabbing the entire table. This can enhance performance and reduce data transfer.

Question:

In the following PySpark code, the df DataFrame is loaded from a database table named "schema.tablename". How can we modify the code to fetch data from the result set of a custom query instead?

from pyspark.sql import SparkSession

spark = SparkSession\
    .builder\
    .appName("spark play")\
    .getOrCreate()    

df = spark.read\
    .format("jdbc")\
    .option("url", "jdbc:mysql://localhost:port")\
    .option("dbtable", "schema.tablename")\
    .option("user", "username")\
    .option("password", "password")\
    .load()

Answer:

To fetch the result set of a custom query, provide the query as the "dbtable" argument in the Spark DataFrameReader's options. The query must be enclosed in parentheses and aliased to a temporary table name.

...
.option("dbtable", "(SELECT foo, bar FROM schema.tablename) AS tmp")
...

By passing the subquery as the "dbtable" argument, Spark will execute the query and load the resulting data into the DataFrame. This allows users to retrieve specific data from external databases without the overhead of fetching the entire table.

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