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https://issues.apache.org/jira/browse/BEAM-8335?focusedWorklogId=361258&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-361258
]
ASF GitHub Bot logged work on BEAM-8335:
----------------------------------------
Author: ASF GitHub Bot
Created on: 18/Dec/19 01:51
Start Date: 18/Dec/19 01:51
Worklog Time Spent: 10m
Work Description: davidyan74 commented on pull request #10405:
[BEAM-8335] Background caching job
URL: https://github.com/apache/beam/pull/10405#discussion_r359116365
##########
File path:
sdks/python/apache_beam/runners/interactive/background_caching_job.py
##########
@@ -0,0 +1,101 @@
+#
+# 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.
+#
+
+"""Module to build and run background caching job.
+
+For internal use only; no backwards-compatibility guarantees.
+
+A background caching job is a job that caches events for all unbounded sources
+of a given pipeline. With Interactive Beam, one such job is started when a
+pipeline run happens (which produces a main job in contrast to the background
+caching job) and meets the following conditions:
+
+ #. The pipeline contains unbounded sources.
+ #. No such background job is running.
+ #. No such background job has completed successfully and the cached events
are
+ still valid (invalidated when unbounded sources change in the pipeline).
+
+Once started, the background caching job runs asynchronously until it hits some
+cache size limit. Meanwhile, the main job and future main jobs from the
pipeline
+will run using the deterministic replay-able cached events until they are
+invalidated.
+"""
+
+from __future__ import absolute_import
+
+import apache_beam as beam
+from apache_beam import runners
+from apache_beam.runners.interactive import interactive_environment as ie
+
+
+def attempt_to_run_background_caching_job(runner, user_pipeline, options=None):
+ """Attempts to run a background caching job for a user-defined pipeline.
+
+ If a background caching job is started, return the pipeline result.
Otherwise,
+ return None.
+ The pipeline result is automatically tracked by Interactive Beam in case
+ future cancellation/cleanup is needed.
+ """
+ if is_background_caching_job_needed(user_pipeline):
+ # Cancel non-terminal jobs if there is any before starting a new one.
+ attempt_to_cancel_background_caching_job(user_pipeline)
+ # TODO(BEAM-8335): refactor background caching job logic from
+ # pipeline_instrument module to this module and aggregate tests.
+ from apache_beam.runners.interactive import pipeline_instrument as instr
+ runner_pipeline = beam.pipeline.Pipeline.from_runner_api(
+ user_pipeline.to_runner_api(use_fake_coders=True),
+ runner,
+ options)
+ background_caching_job_result = beam.pipeline.Pipeline.from_runner_api(
+ instr.pin(runner_pipeline).background_caching_pipeline_proto(),
+ runner,
+ options).run()
+ ie.current_env().set_pipeline_result(user_pipeline,
+ background_caching_job_result,
+ is_main_job=False)
+
+def is_background_caching_job_needed(user_pipeline):
+ """Determines if a background caching job needs to be started."""
+ background_caching_job_result = ie.current_env().pipeline_result(
+ user_pipeline, is_main_job=False)
+ from apache_beam.runners.interactive import pipeline_instrument as instr
+ # Checks if the pipeline contains unbounded sources.
+ return (instr.has_unbounded_sources(user_pipeline) and
Review comment:
This may not be in the scope of this PR, but we also need to let the user
specify their own sources to be cached, because the user may have a large
bounded source that they want to capture a small segment of.
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Issue Time Tracking
-------------------
Worklog Id: (was: 361258)
Time Spent: 49h 20m (was: 49h 10m)
> 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: 49h 20m
> 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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