80bf48f437
## What changes were proposed in this pull request?
This patch provides a first cut of python APIs for structured streaming. This PR provides the new classes:
- ContinuousQuery
- Trigger
- ProcessingTime
in pyspark under `pyspark.sql.streaming`.
In addition, it contains the new methods added under:
- `DataFrameWriter`
a) `startStream`
b) `trigger`
c) `queryName`
- `DataFrameReader`
a) `stream`
- `DataFrame`
a) `isStreaming`
This PR doesn't contain all methods exposed for `ContinuousQuery`, for example:
- `exception`
- `sourceStatuses`
- `sinkStatus`
They may be added in a follow up.
This PR also contains some very minor doc fixes in the Scala side.
## How was this patch tested?
Python doc tests
TODO:
- [ ] verify Python docs look good
Author: Burak Yavuz <brkyvz@gmail.com>
Author: Burak Yavuz <burak@databricks.com>
Closes #12320 from brkyvz/stream-python.
125 lines
4.2 KiB
Python
125 lines
4.2 KiB
Python
#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# 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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from abc import ABCMeta, abstractmethod
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from pyspark import since
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__all__ = ["ContinuousQuery"]
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class ContinuousQuery(object):
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"""
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A handle to a query that is executing continuously in the background as new data arrives.
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All these methods are thread-safe.
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.. note:: Experimental
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.. versionadded:: 2.0
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"""
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def __init__(self, jcq, sqlContext):
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self._jcq = jcq
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self._sqlContext = sqlContext
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@property
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@since(2.0)
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def name(self):
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"""The name of the continuous query.
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"""
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return self._jcq.name()
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@property
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@since(2.0)
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def isActive(self):
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"""Whether this continuous query is currently active or not.
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"""
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return self._jcq.isActive()
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@since(2.0)
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def awaitTermination(self, timeoutMs=None):
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"""Waits for the termination of `this` query, either by :func:`query.stop()` or by an
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exception. If the query has terminated with an exception, then the exception will be thrown.
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If `timeoutMs` is set, it returns whether the query has terminated or not within the
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`timeoutMs` milliseconds.
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If the query has terminated, then all subsequent calls to this method will either return
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immediately (if the query was terminated by :func:`stop()`), or throw the exception
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immediately (if the query has terminated with exception).
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throws ContinuousQueryException, if `this` query has terminated with an exception
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"""
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if timeoutMs is not None:
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if type(timeoutMs) != int or timeoutMs < 0:
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raise ValueError("timeoutMs must be a positive integer. Got %s" % timeoutMs)
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return self._jcq.awaitTermination(timeoutMs)
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else:
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return self._jcq.awaitTermination()
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@since(2.0)
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def processAllAvailable(self):
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"""Blocks until all available data in the source has been processed an committed to the
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sink. This method is intended for testing. Note that in the case of continually arriving
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data, this method may block forever. Additionally, this method is only guaranteed to block
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until data that has been synchronously appended data to a stream source prior to invocation.
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(i.e. `getOffset` must immediately reflect the addition).
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"""
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return self._jcq.processAllAvailable()
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@since(2.0)
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def stop(self):
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"""Stop this continuous query.
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"""
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self._jcq.stop()
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class Trigger(object):
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"""Used to indicate how often results should be produced by a :class:`ContinuousQuery`.
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.. note:: Experimental
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.. versionadded:: 2.0
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"""
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__metaclass__ = ABCMeta
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@abstractmethod
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def _to_java_trigger(self, sqlContext):
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"""Internal method to construct the trigger on the jvm.
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"""
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pass
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class ProcessingTime(Trigger):
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"""A trigger that runs a query periodically based on the processing time. If `interval` is 0,
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the query will run as fast as possible.
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The interval should be given as a string, e.g. '2 seconds', '5 minutes', ...
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.. note:: Experimental
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.. versionadded:: 2.0
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"""
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def __init__(self, interval):
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if interval is None or type(interval) != str or len(interval.strip()) == 0:
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raise ValueError("interval should be a non empty interval string, e.g. '2 seconds'.")
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self.interval = interval
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def _to_java_trigger(self, sqlContext):
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return sqlContext._sc._jvm.org.apache.spark.sql.ProcessingTime.create(self.interval)
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