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80 lines
3.0 KiB
Python
80 lines
3.0 KiB
Python
################################################################################
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# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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################################################################################
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import io
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from pyflink.serializers import IterableSerializer
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from pyflink.table.utils import arrow_to_pandas, pandas_to_arrow
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class ArrowSerializer(IterableSerializer):
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"""
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Serializes pandas.Series into Arrow streaming format data.
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"""
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def __init__(self, schema, row_type, timezone):
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super(ArrowSerializer, self).__init__()
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self._schema = schema
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self._field_types = row_type.field_types()
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self._timezone = timezone
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def __repr__(self):
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return "ArrowSerializer"
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def serialize(self, iterable, stream):
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writer = None
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try:
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for cols in iterable:
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batch = pandas_to_arrow(self._schema, self._timezone, self._field_types, cols)
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if writer is None:
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import pyarrow as pa
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writer = pa.RecordBatchStreamWriter(stream, batch.schema)
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writer.write_batch(batch)
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finally:
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if writer is not None:
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writer.close()
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def deserialize(self, stream):
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import pyarrow as pa
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reader = pa.ipc.open_stream(stream)
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for batch in reader:
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yield arrow_to_pandas(self._timezone, self._field_types, [batch])
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def load_from_iterator(self, iter):
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class IteratorIO(io.RawIOBase):
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def __init__(self, iter):
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super(IteratorIO, self).__init__()
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self.iter = iter
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self.leftover = None
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def readable(self):
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return True
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def readinto(self, b):
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output_buffer_len = len(b)
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input = self.leftover or (self.iter.next() if self.iter.hasNext() else None)
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if input is None:
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return 0
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output, self.leftover = input[:output_buffer_len], input[output_buffer_len:]
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b[:len(output)] = output
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return len(output)
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import pyarrow as pa
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reader = pa.ipc.open_stream(
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io.BufferedReader(IteratorIO(iter), buffer_size=io.DEFAULT_BUFFER_SIZE))
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for batch in reader:
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yield batch
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