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https://issues.apache.org/jira/browse/SPARK-45639?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Allison Wang updated SPARK-45639:
---------------------------------
Description:
Allow users to read from a Python data source using
`spark.read.format(...).load()` in PySpark. For example
Users can extend the DataSource and the DataSourceReader classes to create
their own Python data source reader and use them in PySpark:
{code:java}
class MyReader(DataSourceReader):
def read(self, partition):
yield (0, 1)
class MyDataSource(DataSource):
def schema(self):
return "id INT, value INT"
def reader(self, schema):
return MyReader()
df = spark.read.format("MyDataSource").load()
df.show()
+---+-----+
| id|value|
+---+-----+
| 0| 1|
+---+-----+
{code}
was:
Allow users to read from a Python data source using
`spark.read.format(...).load()`
For example
Users can extend the DataSource and the DataSourceReader classes to create
their own Python data source reader and use them in PySpark:
{code:java}
class MyReader(DataSourceReader):
def read(self, partition):
yield (0, 1)
class MyDataSource(DataSource):
def schema(self):
return "id INT, value INT"
def reader(self, schema):
return MyReader()
df = spark.read.format("MyDataSource").load()
df.show()
+---+-----+
| id|value|
+---+-----+
| 0| 1|
+---+-----+
{code}
> Support loading Python data sources in DataFrameReader
> ------------------------------------------------------
>
> Key: SPARK-45639
> URL: https://issues.apache.org/jira/browse/SPARK-45639
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark
> Affects Versions: 4.0.0
> Reporter: Allison Wang
> Priority: Major
>
> Allow users to read from a Python data source using
> `spark.read.format(...).load()` in PySpark. For example
> Users can extend the DataSource and the DataSourceReader classes to create
> their own Python data source reader and use them in PySpark:
> {code:java}
> class MyReader(DataSourceReader):
> def read(self, partition):
> yield (0, 1)
> class MyDataSource(DataSource):
> def schema(self):
> return "id INT, value INT"
>
> def reader(self, schema):
> return MyReader()
> df = spark.read.format("MyDataSource").load()
> df.show()
> +---+-----+
> | id|value|
> +---+-----+
> | 0| 1|
> +---+-----+
> {code}
>
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