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https://issues.apache.org/jira/browse/BEAM-2953?focusedWorklogId=155610&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-155610
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ASF GitHub Bot logged work on BEAM-2953:
----------------------------------------
Author: ASF GitHub Bot
Created on: 17/Oct/18 21:08
Start Date: 17/Oct/18 21:08
Worklog Time Spent: 10m
Work Description: akedin commented on a change in pull request #6540:
[BEAM-2953] Advanced Timeseries examples.
URL: https://github.com/apache/beam/pull/6540#discussion_r226095495
##########
File path:
sdks/java/extensions/timeseries/src/main/java/org/apache/beam/sdk/extensions/timeseries/transforms/OrderOutput.java
##########
@@ -0,0 +1,388 @@
+/*
+ * 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.
+ */
+
+package org.apache.beam.sdk.extensions.timeseries.transforms;
+
+import com.google.common.collect.Lists;
+import com.google.protobuf.util.Durations;
+import com.google.protobuf.util.Timestamps;
+import java.util.Iterator;
+import java.util.List;
+import org.apache.beam.sdk.annotations.Experimental;
+import org.apache.beam.sdk.extensions.protobuf.ProtoCoder;
+import org.apache.beam.sdk.extensions.timeseries.TimeSeriesOptions;
+import org.apache.beam.sdk.extensions.timeseries.configuration.TSConfiguration;
+import org.apache.beam.sdk.extensions.timeseries.protos.TimeSeriesData;
+import org.apache.beam.sdk.extensions.timeseries.utils.TSAccums;
+import org.apache.beam.sdk.state.BagState;
+import org.apache.beam.sdk.state.StateSpec;
+import org.apache.beam.sdk.state.StateSpecs;
+import org.apache.beam.sdk.state.TimeDomain;
+import org.apache.beam.sdk.state.Timer;
+import org.apache.beam.sdk.state.TimerSpec;
+import org.apache.beam.sdk.state.TimerSpecs;
+import org.apache.beam.sdk.state.ValueState;
+import org.apache.beam.sdk.transforms.DoFn;
+import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.ParDo;
+import org.apache.beam.sdk.transforms.windowing.*;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.PCollection;
+import org.joda.time.Duration;
+import org.joda.time.Instant;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+/** Create ordered output from the fixed windowed aggregations. */
+@SuppressWarnings("serial")
+@Experimental
+public class OrderOutput
+ extends PTransform<
+ PCollection<KV<TimeSeriesData.TSKey, TimeSeriesData.TSAccum>>,
+ PCollection<KV<TimeSeriesData.TSKey, TimeSeriesData.TSAccum>>> {
+
+ private static final Logger LOG = LoggerFactory.getLogger(OrderOutput.class);
+
+ @Override
+ public PCollection<KV<TimeSeriesData.TSKey, TimeSeriesData.TSAccum>> expand(
+ PCollection<KV<TimeSeriesData.TSKey, TimeSeriesData.TSAccum>> input) {
+
+ TSConfiguration options =
+ TSConfiguration.createConfigurationFromOptions(
+ input.getPipeline().getOptions().as(TimeSeriesOptions.class));
+
+ // Move into Global Time Domain, this allows Keyed State to retain its
value across windows.
+ // Late Data is dropped at this stage.
+
+ PCollection<KV<TimeSeriesData.TSKey, TimeSeriesData.TSAccum>>
windowNoLateData =
+ input.apply(
+ "Global Window",
+ Window.<KV<TimeSeriesData.TSKey, TimeSeriesData.TSAccum>>into(new
GlobalWindows())
+ .withAllowedLateness(Duration.ZERO));
+
+ return windowNoLateData
+ .apply(ParDo.of(new GetPreviousData(options)))
+ .apply(
+ "Re Window post Global",
+ Window.<KV<TimeSeriesData.TSKey, TimeSeriesData.TSAccum>>into(
+ FixedWindows.of(options.downSampleDuration()))
+ // TODO: DirectRunner not showing results with exact late date
match
+
//.withAllowedLateness(options.downSampleDuration().plus(options.downSampleDuration()))
+ .withAllowedLateness(Duration.standardDays(1))
+ .discardingFiredPanes());
+ }
+
+ /**
+ * When a new key is seen (state == null) for the first time, we will create
a timer to fire in
+ * the next window boundary. If this is not the first time the key is seen
we check the ttl to see
+ * if a new timer is required. In-between timers firing, we will add all new
elements to a List.
+ * lets have 3 elements coming in at various time and then there is NULL for
forth time slice
+ * [t1,t2,t3, NULL] t1 arrives and we set timer to fire at
t1.plus(downsample duration + fixed
+ * offset).
+ *
+ * <p>Then we have state.set(t1). t2 arrives and we add t1 to t2 as the
previous value and we
+ * output the value state.set(t2)
+ *
+ * <p>t3 arrives and we add t2 to t3 as the previous value and we output the
value state.set(t3)
+ *
+ * <p>at time 4 we have no entry, here we use the last known state which is
t3 and we change the
+ * time values.
+ *
+ * <p>NOTE: Need to see if this is really needed In case there is more than
one element arriving
+ * before the timer fires, we will also hold a List of elements If the list
of elements is > 0
+ * then we loop through the core logic until the list is exhausted
+ */
+ @Experimental
+ public static class GetPreviousData
+ extends DoFn<
+ KV<TimeSeriesData.TSKey, TimeSeriesData.TSAccum>,
+ KV<TimeSeriesData.TSKey, TimeSeriesData.TSAccum>> {
+
+ TSConfiguration options;
+
+ private GetPreviousData(TSConfiguration configuration) {
+ this.options = configuration;
+ }
+
+ // Setup our state objects
+
+ @StateId("lastKnownState")
+ private final StateSpec<ValueState<TimeSeriesData.TSAccum>> lastKnownState
=
+ StateSpecs.value(ProtoCoder.of(TimeSeriesData.TSAccum.class));
+
+ @StateId("holdingList")
+ private final StateSpec<BagState<TimeSeriesData.TSAccum>> holdingList =
+ StateSpecs.bag(ProtoCoder.of(TimeSeriesData.TSAccum.class));
+
+ @TimerId("alarm")
+ private final TimerSpec alarm = TimerSpecs.timer(TimeDomain.EVENT_TIME);
+
+ /**
+ * This is the simple path... A new element is here so we add it to the
list of elements and set
+ * a timer
+ *
+ * @param c
+ * @param holdingList
+ * @param timer
+ */
+ @ProcessElement
+ public void processElement(
+ ProcessContext c,
+ @StateId("holdingList") BagState<TimeSeriesData.TSAccum> holdingList,
+ @TimerId("alarm") Timer timer) {
+
+ Instant alarm = c.timestamp().plus(options.downSampleDuration());
+
+ timer.set(alarm);
Review comment:
Do I understand it right that for all incoming elements we will set alarms?
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Issue Time Tracking
-------------------
Worklog Id: (was: 155610)
Time Spent: 3h 20m (was: 3h 10m)
> Timeseries processing extensions using state API
> ------------------------------------------------
>
> Key: BEAM-2953
> URL: https://issues.apache.org/jira/browse/BEAM-2953
> Project: Beam
> Issue Type: Improvement
> Components: sdk-ideas
> Affects Versions: 2.7.0
> Reporter: Reza ardeshir rokni
> Assignee: Reuven Lax
> Priority: Minor
> Time Spent: 3h 20m
> Remaining Estimate: 0h
>
> A general set of timeseries transforms that abstract the user from the
> process of dealing with some of the common problems when dealing with
> timeseries using BEAM (in stream or batch mode).
> BEAM can be used to build out some very interesting pre-processing stages for
> time series data. Some examples that will be useful:
> - Downsampling time series based on simple MIN, MAX, COUNT, SUM, LAST, FIRST
> - Creating a value for each downsampled window even if no value has been
> emitted for the specific key.
> - Loading the value of a downsample with the previous value (used in FX with
> previous close being brought into current open value)
>
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