How Can I Retrieve Specific Query Results Instead of Entire Tables in Apache Spark 2.0.0?

Retrieving Query Results Instead of Table Data in Apache Spark 2.0.0

In Apache Spark 2.0.0, it is possible to fetch a specific query result set from an external database, rather than loading the entire table into Spark. This can be useful for optimizing performance and reducing the amount of data processed by your Spark application.

Using PySpark, you can specify a subquery as the dbtable argument for the read method. This subquery will be executed on the external database and the resulting data will be loaded into Spark. For example, the following code demonstrates how to retrieve the results of a query instead of loading the entire schema.tablename table:

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", "(SELECT foo, bar FROM schema.tablename) AS tmp")\
    .option("user", "username")\
    .option("password", "password")\
    .load()

By specifying the subquery as the dbtable argument, you can select only the specific columns and rows that you are interested in. This can result in significant performance improvements, especially when dealing with large tables.

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