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  1. Issue Analysis
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  3. Spark Scala

SPRKSCL1100

org.apache.spark.sql.DataFrame.repartition

PreviousSPRKSCL1002NextSPRKSCL1101

Last updated 5 months ago

This issue code has been deprecated since

Message: Repartition is not supported.

Category: Parsing error.

Description

This issue appears when the SMA detects a use of the function, which is not supported by Snowpark. Snowflake manages the storage and the workload on the clusters making repartition operation inapplicable.

Scenario

Input

Below is an example of the org.apache.spark.sql.DataFrame.repartition function used to return a new DataFrame partitioned by the given partitioning expressions.

    var nameData = Seq("James", "Sarah", "Dylan", "Leila, "Laura", "Peter")
    var jobData = Seq("Police", "Doctor", "Actor", "Teacher, "Dentist", "Fireman")
    var ageData = Seq(40, 38, 34, 27, 29, 55)

    val dfName = nameData.toDF("name")
    val dfJob = jobData.toDF("job")
    val dfAge = ageData.toDF("age")

    val dfRepartitionByExpresion = dfName.repartition($"name")

    val dfRepartitionByNumber = dfJob.repartition(3)

    val dfRepartitionByBoth = dfAge.repartition(3, $"age")

    val joinedDf = dfRepartitionByExpresion.join(dfRepartitionByNumber)

Output

The SMA adds the EWI SPRKSCL1100 to the output code to let you know that this function is not supported by Snowpark.

    var nameData = Seq("James", "Sarah", "Dylan", "Leila, "Laura", "Peter")
    var jobData = Seq("Police", "Doctor", "Actor", "Teacher, "Dentist", "Fireman")
    var ageData = Seq(40, 38, 34, 27, 29, 55)

    val dfName = nameData.toDF("name")
    val dfJob = jobData.toDF("job")
    val dfAge = ageData.toDF("age")

    /*EWI: SPRKSCL1100 => Repartition is not supported*/
    val dfRepartitionByExpresion = dfName.repartition($"name")

    /*EWI: SPRKSCL1100 => Repartition is not supported*/
    val dfRepartitionByNumber = dfJob.repartition(3)

    /*EWI: SPRKSCL1100 => Repartition is not supported*/
    val dfRepartitionByBoth = dfAge.repartition(3, $"age")

    val joinedDf = dfRepartitionByExpresion.join(dfRepartitionByNumber)

Recommended Fix

Since Snowflake manages the storage and the workload on the clusters making repartition operation inapplicable. This means that the use of repartition before the join is not required at all.

    var nameData = Seq("James", "Sarah", "Dylan", "Leila, "Laura", "Peter")
    var jobData = Seq("Police", "Doctor", "Actor", "Teacher, "Dentist", "Fireman")
    var ageData = Seq(40, 38, 34, 27, 29, 55)

    val dfName = nameData.toDF("name")
    val dfJob = jobData.toDF("job")
    val dfAge = ageData.toDF("age")

    val dfRepartitionByExpresion = dfName

    val dfRepartitionByNumber = dfJob

    val dfRepartitionByBoth = dfAge

    val joinedDf = dfRepartitionByExpresion.join(dfRepartitionByNumber)

Additional recommendations

The provides insight about Snowflake storage management.

Snowpark could be useful in how to adapt a particular scenario without the need of repartition.

For more support, you can email us at or post an issue .

Spark Conversion Core 2.3.22
org.apache.spark.sql.DataFrame.repartition
Snowflake's architecture guide
Dataframe reference
sma-support@snowflake.com
in the SMA