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Posted to issues@spark.apache.org by "Allison Wang (Jira)" <ji...@apache.org> on 2023/10/23 20:56:00 UTC
[jira] [Updated] (SPARK-45639) Support Python data source in DataFrameReader

     [ https://issues.apache.org/jira/browse/SPARK-45639?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Allison Wang updated SPARK-45639:
---------------------------------
    Description: 
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()
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:
```python
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|
+---+-----+
```


> Support Python data source 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()`
> 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()
> df.show()
> +---+-----+
> | id|value|
> +---+-----+
> |  0|    1|
> +---+-----+
> {code}
>  



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