Performance improvements with pushdown - Amazon Redshift
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Amazon Redshift will no longer support the creation of new Python UDFs starting November 1, 2025. If you would like to use Python UDFs, create the UDFs prior to that date. Existing Python UDFs will continue to function as normal. For more information, see the blog post .

Performance improvements with pushdown

The Spark connector automatically applies predicate and query pushdown to optimize for performance. This support means that if you’re using a supported function in your query, the Spark connector will turn the function into a SQL query and run the query in Amazon Redshift. This optimization results in less data being retrieved, so Apache Spark can process less data and have better performance. By default, pushdown is automatically activated. To deactivate it, set autopushdown to false. 

import sqlContext.implicits._val 
 sample= sqlContext.read
    .format("io.github.spark_redshift_community.spark.redshift")
    .option("url",jdbcURL )
    .option("tempdir", tempS3Dir)
    .option("dbtable", "event")
    .option("autopushdown", "false")
    .load()

The following functions are supported with pushdown. If you’re using a function that’s not in this list, the Spark connector will perform the function in Spark instead of Amazon Redshift, resulting in unoptimized performance. For a complete list of functions in Spark, see Built-in Functions.

  • Aggregation functions

    • avg

    • count

    • max

    • min

    • sum

    • stddev_samp

    • stddev_pop

    • var_samp

    • var_pop

  • Boolean operators

    • in

    • isnull

    • isnotnull

    • contains

    • endswith

    • startswith

  • Logical operators

    • and

    • or

    • not (or !)

  • Mathematical functions

    • +

    • -

    • *

    • /

    • - (unary)

    • abs

    • acos

    • asin

    • atan

    • ceil

    • cos

    • exp

    • floor

    • greatest

    • least

    • log10

    • pi

    • pow

    • round

    • sin

    • sqrt

    • tan

  • Miscellaneous functions

    • cast

    • coalesce

    • decimal

    • if

    • in

  • Relational operators

    • !=

    • =

    • >

    • >=

    • <

    • <=

  • String functions

    • ascii

    • lpad

    • rpad

    • translate

    • upper

    • lower

    • length

    • trim

    • ltrim

    • rtrim

    • like

    • substring

    • concat

  • Time and date functions

    • add_months

    • date

    • date_add

    • date_sub

    • date_trunc

    • timestamp

    • trunc

  • Mathematical operations

    • CheckOverflow

    • PromotePrecision

  • Relational operations

    • Aliases (for example, AS)

    • CaseWhen

    • Distinct

    • InSet

    • Joins and cross joins

    • Limits

    • Unions, union all

    • ScalarSubquery

    • Sorts (ascending and descending)

    • UnscaledValue