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https://issues.apache.org/jira/browse/BEAM-8335?focusedWorklogId=393933&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-393933
]
ASF GitHub Bot logged work on BEAM-8335:
----------------------------------------
Author: ASF GitHub Bot
Created on: 27/Feb/20 03:14
Start Date: 27/Feb/20 03:14
Worklog Time Spent: 10m
Work Description: rohdesamuel commented on pull request #10915:
[BEAM-8335] Add PCollection to DataFrame logic for InteractiveRunner.
URL: https://github.com/apache/beam/pull/10915#discussion_r384892377
##########
File path: sdks/python/apache_beam/runners/interactive/utils.py
##########
@@ -0,0 +1,112 @@
+#
+# 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.
+#
+
+"""Utilities to be used in Interactive Beam.
+"""
+
+from __future__ import absolute_import
+
+import pandas as pd
+
+from apache_beam.typehints import typehints as th
+from apache_beam.utils.windowed_value import WindowedValue
+
+COLUMN_PREFIX = 'el'
+
+
+def parse_row_(el, element_type, depth):
+ elements = []
+ columns = []
+
+ # Recurse if there are a known length of columns to parse into.
+ if isinstance(element_type, (th.TupleHint.TupleConstraint)):
+ for index, t in enumerate(element_type._inner_types()):
+ underlying_columns, underlying_elements = parse_row_(el[index], t,
+ depth + 1)
+ column = '[{}]'.format(index)
+ if underlying_columns:
+ columns += [column + c for c in underlying_columns]
+ else:
+ columns += [column]
+ elements += underlying_elements
+
+ # Don't make new columns for variable length types.
+ elif isinstance(
+ element_type,
+ (th.ListHint.ListConstraint, th.TupleHint.TupleSequenceConstraint)):
+ elements = [pd.array(el)]
+
+ # For any other types, try to parse as a namedtuple, otherwise pass element
+ # through.
+ else:
+ fields = getattr(el, '_fields', None)
+ if fields:
+ columns = list(fields)
+ if depth > 0:
+ columns = ['[{}]'.format(f) for f in fields]
+ elements = [el._asdict()[f] for f in fields]
+ else:
+ elements = [el]
+ return columns, elements
+
+
+def parse_row(el, element_type, include_window_info=True,
prefix=COLUMN_PREFIX):
+ # Reify the WindowedValue data to the Dataframe if asked.
+ windowed = None
+ if isinstance(el, WindowedValue):
+ if include_window_info:
+ windowed = el
+ el = el.value
+
+ # Parse the elements with the given type.
+ columns, elements = parse_row_(el, element_type, 0)
+
+ # If there are no columns returned, there is only a single column of a
+ # primitive data type.
+ if not columns:
+ columns = ['']
+
+ # Add the prefix to the columns that have an index.
+ for i in range(len(columns)):
+ if columns[i] == '' or columns[i][0] == '[':
Review comment:
This code was removed in a recent commit.
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Issue Time Tracking
-------------------
Worklog Id: (was: 393933)
Time Spent: 76h 10m (was: 76h)
> 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: 76h 10m
> 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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