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[FLINK-13811][python] Support converting flink Table to pandas DataFrame #12148

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@dianfu dianfu commented May 14, 2020

What is the purpose of the change

This pull request add support to convert flink Table to pandas DataFrame

Brief change log

  • Add utility ArrowUtils.collectAsPandasDataFrame to materialize the results of the table and serialize them into arrow format
  • Add Table.to_pandas in PyFlink to convert flink Table to pandas DataFrame

Verifying this change

This change added tests and can be verified as follows:

  • Added tests test_pandas_conversion.test_to_pandas and test_pandas_conversion.test_empty_to_pandas

Does this pull request potentially affect one of the following parts:

  • Dependencies (does it add or upgrade a dependency): (no)
  • The public API, i.e., is any changed class annotated with @Public(Evolving): (no)
  • The serializers: (no)
  • The runtime per-record code paths (performance sensitive): (no)
  • Anything that affects deployment or recovery: JobManager (and its components), Checkpointing, Kubernetes/Yarn/Mesos, ZooKeeper: (no)
  • The S3 file system connector: (no)

Documentation

  • Does this pull request introduce a new feature? (yes)
  • If yes, how is the feature documented? (docs)

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zjffdu commented May 14, 2020

@dianfu Is arrow a dependency of pyflink ? I mean whether arrow will be installed when running pip install apache_flink

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dianfu commented May 14, 2020

Yes, it will be installed when running pip install apache_flink

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@dianfu Thanks for your PR! Looks good overall, just some minor comments.


## Convert PyFlink Table to Pandas DataFrame

It also supports to convert a PyFlink Table to a Pandas DataFrame. Internally, it will materialize the results of the
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supports to convert -> supports converting?

## Convert PyFlink Table to Pandas DataFrame

It also supports to convert a PyFlink Table to a Pandas DataFrame. Internally, it will materialize the results of the
table and serialize them into multiple arrow batches of Arrow columnar format at client side. The maximum arrow batch size
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arrow -> Arrow?


def load_from_iterator(self, itor):
class IteratorIO(io.RawIOBase):
def __init__(self, itor):
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add super().init() method?


private static boolean isBlinkPlanner(Table table) {
TableEnvironment tableEnv = ((TableImpl) table).getTableEnvironment();
if (tableEnv instanceof BatchTableEnvironment || tableEnv instanceof TableEnvImpl) {
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The tableEnv instanceof BatchTableEnvironment is unnecessary.

// The SelectTableSink of blink planner will convert the table schema and we
// need to keep the table schema used here be consistent with the converted table schema
TableSchema convertedTableSchema = SelectTableSinkSchemaConverter.changeDefaultConversionClass(table.getSchema());
DataFormatConverters.DataFormatConverter converter = DataFormatConverters.getConverterForDataType(convertedTableSchema.toRowDataType());
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Break this line as it is too long?

def test_to_pandas(self):
table = self.t_env.from_pandas(self.pdf, self.data_type)
result_pdf = table.to_pandas()
self.assertTrue(2, len(result_pdf))
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assertEqual?

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dianfu commented May 15, 2020

@WeiZhong94 Thanks for the review. The test failures are instable cases of Kafka which are not related to this PR. Merging...

@dianfu dianfu closed this in d417889 May 15, 2020
@dianfu dianfu deleted the FLINK-13811 branch June 10, 2020 03:05
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