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https://issues.apache.org/jira/browse/BEAM-8335?focusedWorklogId=335670&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-335670
]
ASF GitHub Bot logged work on BEAM-8335:
----------------------------------------
Author: ASF GitHub Bot
Created on: 29/Oct/19 18:31
Start Date: 29/Oct/19 18:31
Worklog Time Spent: 10m
Work Description: robertwb commented on pull request #9720: [BEAM-8335]
Add initial modules for interactive streaming support
URL: https://github.com/apache/beam/pull/9720#discussion_r340251733
##########
File path:
sdks/python/apache_beam/runners/interactive/caching/streaming_cache.py
##########
@@ -0,0 +1,124 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+from __future__ import absolute_import
+
+from apache_beam.portability.api.beam_interactive_api_pb2 import
InteractiveStreamHeader
+from apache_beam.portability.api.beam_interactive_api_pb2 import
InteractiveStreamRecord
+from apache_beam.portability.api.beam_runner_api_pb2 import TestStreamPayload
+from apache_beam.utils import timestamp
+from apache_beam.utils.timestamp import Timestamp
+
+
+class StreamingCache(object):
+ """Abstraction that holds the logic for reading and writing to cache.
+ """
+ def __init__(self, readers):
+ self._readers = readers
+
+ class Reader(object):
+ """Abstraction that reads from PCollection readers.
+
+ This class is an Abstraction layer over multiple PCollection readers to be
+ used for supplying the Interactive Service with TestStream events.
+
+ This class is also responsible for holding the state of the clock,
injecting
+ clock advancement events, and watermark advancement events.
+ """
+ def __init__(self, readers):
+ self._timestamp = Timestamp.of(0)
+ self._readers = {}
+ self._headers = {}
+ readers = [r.read() for r in readers]
+
+ # The header allows for metadata about an entire stream, so that the data
+ # isn't copied per record.
+ for r in readers:
+ header = InteractiveStreamHeader()
+ header.ParseFromString(next(r))
+
+ # Main PCollections in Beam have a tag as None. Deserializing a Proto
+ # with an empty tag becomes an empty string. Here we normalize to what
+ # Beam expects.
+ self._headers[header.tag if header.tag else None] = header
+ self._readers[header.tag if header.tag else None] = r
+
+ self._watermarks = {tag: timestamp.MIN_TIMESTAMP for tag in
self._headers}
+
+ def read(self):
+ """Reads records from PCollection readers.
+ """
+ records = {}
+ for tag, r in self._readers.items():
+ try:
+ record = InteractiveStreamRecord()
+ record.ParseFromString(next(r))
+ records[tag] = record
+ except StopIteration:
+ pass
+
+ events = []
+ if not records:
+ self.advance_watermark(timestamp.MAX_TIMESTAMP, events)
+
+ records = sorted(records.items(), key=lambda x: x[1].processing_time)
+ for tag, r in records:
+ # We always send the processing time event first so that the TestStream
+ # can sleep so as to emulate the original stream.
+ self.advance_processing_time(
+ Timestamp.from_proto(r.processing_time), events)
+ self.advance_watermark(Timestamp.from_proto(r.watermark), events,
+ tag=tag)
+
+ events.append(TestStreamPayload.Event(
+ element_event=TestStreamPayload.Event.AddElements(
+ elements=[r.element], tag=tag)))
+ return events
+
+ def advance_processing_time(self, processing_time, events):
+ """Advances the internal clock state and injects an AdvanceProcessingTime
+ event.
+ """
+ if self._timestamp != processing_time:
+ duration = timestamp.Duration(
+ micros=processing_time.micros - self._timestamp.micros)
+
+ self._timestamp = processing_time
+ processing_time_event = TestStreamPayload.Event.AdvanceProcessingTime(
+ advance_duration=duration.micros)
+ events.append(TestStreamPayload.Event(
+ processing_time_event=processing_time_event))
+
+ def advance_watermark(self, watermark, events, tag=None):
+ """Advances the internal clock state and injects an AdvanceWatermark
+ event.
+ """
+ if self._watermarks[tag] < watermark:
+ self._watermarks[tag] = watermark
+ payload = TestStreamPayload.Event(
+ watermark_event=TestStreamPayload.Event.AdvanceWatermark(
+ new_watermark=self._watermarks[tag].micros, tag=tag))
+ events.append(payload)
+
+ def stream_time(self):
+ return self._timestamp
+
+ def watermark(self):
Review comment:
Why is this needed?
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Issue Time Tracking
-------------------
Worklog Id: (was: 335670)
Time Spent: 11h 50m (was: 11h 40m)
> Add streaming support to Interactive Beam
> -----------------------------------------
>
> Key: BEAM-8335
> URL: https://issues.apache.org/jira/browse/BEAM-8335
> Project: Beam
> Issue Type: Improvement
> Components: runner-py-interactive
> Reporter: Sam Rohde
> Assignee: Sam Rohde
> Priority: Major
> Time Spent: 11h 50m
> Remaining Estimate: 0h
>
> This issue tracks the work items to introduce streaming support to the
> Interactive Beam experience. This will allow users to:
> * Write and run a streaming job in IPython
> * Automatically cache records from unbounded sources
> * Add a replay experience that replays all cached records to simulate the
> original pipeline execution
> * Add controls to play/pause/stop/step individual elements from the cached
> records
> * Add ability to inspect/visualize unbounded PCollections
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