spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Apache Spark (JIRA)" <>
Subject [jira] [Assigned] (SPARK-24256) ExpressionEncoder should support user-defined types as fields of Scala case class and tuple
Date Sat, 12 May 2018 06:21:00 GMT


Apache Spark reassigned SPARK-24256:

    Assignee:     (was: Apache Spark)

> ExpressionEncoder should support user-defined types as fields of Scala case class and
> -------------------------------------------------------------------------------------------
>                 Key: SPARK-24256
>                 URL:
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.3.0
>            Reporter: Fangshi Li
>            Priority: Major
> Right now, ExpressionEncoder supports ser/de of primitive types, as well as scala case
class, tuple and java bean class. Spark's Dataset natively supports these mentioned types,
but we find Dataset is not flexible for other user-defined types and encoders.
> For example, spark-avro has an AvroEncoder for ser/de Avro types in Dataset. Although
we can use AvroEncoder to define Dataset with types being the Avro Generic or Specific Record,
using such Avro typed Dataset has many limitations: 
>  1. We can not use joinWith on this Dataset since the result is a tuple, but Avro types
cannot be the field of this tuple.
>  2. We can not use some type-safe aggregation methods on this Dataset, such as KeyValueGroupedDataset's
reduceGroups, since the result is also a tuple.
>  3. We cannot augment an Avro SpecificRecord with additional primitive fields together
in a case class, which we find is a very common use case.
> The limitation that Spark does not support define a Scala case class/tuple with subfields
being any other user-defined type, is because ExpressionEncoder does not discover the implicit
Encoder for the user-defined field types, thus can not use any Encoder to serde the user-defined
fields in case class/tuple.
> To address this issue, we propose a trait as a contract(between ExpressionEncoder and
any other user-defined Encoder) to enable case class/tuple/java bean's ExpressionEncoder to
discover the serializer/deserializer/schema from the Encoder of the user-defined type.
> With this proposed patch and our minor modification in AvroEncoder, we remove these
limitations with cluster-default conf
= com.databricks.spark.avro.AvroEncoder$
> This is a patch we have implemented internally and has been used for a few quarters.
We want to propose to upstream as we think this is a useful feature to make Dataset more flexible
to user types.

This message was sent by Atlassian JIRA

To unsubscribe, e-mail:
For additional commands, e-mail:

View raw message