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[BEAM-2039] Number programming guide chapters#320

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asfgit merged 2 commits intoapache:asf-sitefrom
melap:linecleanup
Sep 22, 2017
Merged

[BEAM-2039] Number programming guide chapters#320
asfgit merged 2 commits intoapache:asf-sitefrom
melap:linecleanup

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@melap
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@melap melap commented Sep 15, 2017

Includes the following consistency/formatting changes:

  • Number chapters of programming guide (Re: BEAM-2039). I couldn't figure out how to make the table of contents use 1. 1.1. 1.1.1 etc. for each page, so I have it pulling from the section titles but it unfortunately still has the bullets. any ideas on how to do this better are welcome.
  • Make capitalization of section titles consistent
  • Format text to be more consistent, reasonable line length (no more 500+ character lines)
  • Use the consistent automatic anchor link naming based on section title instead of making our own for arbitrary sections. the auto-generated toc did not work with our hard coded anchors either.

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asfgit commented Sep 15, 2017

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asfgit commented Sep 15, 2017

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melap commented Sep 18, 2017

R: @kennknowles
CC: @xumingmin

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Meaningful content changes are deferrable to future changes.

@@ -1710,21 +2501,27 @@ If our trigger is set to `.accumulatingFiredPanes`, the trigger emits the follow
```


##### Discarding Mode
##### 8.4.1.2. Discarding mode:
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aaaaaaaaaaaaaaaaaaaaaa


##### 4.2.4.6. Combining values in a key-grouped collection
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'in a keyed PCollection'?

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done

* [Pre-written Beam transforms for Java]({{ site.baseurl }}/documentation/sdks/javadoc/{{ site.release_latest }}/index.html?org/apache/beam/sdk/transforms/package-summary.html)
* [Pre-written Beam transforms for Python]({{ site.baseurl }}/documentation/sdks/pydoc/{{ site.release_latest }}/apache_beam.transforms.html)

### An example of a composite transform
#### 4.6.1. Composite transform example
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I think this is too robotic and the previous is too verbose; maybe

'An example [composite ]transform'

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done


When you create a pipeline, you often need to read data from some external source, such as a file in external data sink or a database. Likewise, you may want your pipeline to output its result data to a similar external data sink. Beam provides read and write transforms for a [number of common data storage types]({{site.baseurl }}/documentation/io/built-in/). If you want your pipeline to read from or write to a data storage format that isn't supported by the built-in transforms, you can [implement your own read and write transforms]({{site.baseurl }}/documentation/io/io-toc/).
When you create a new `PTransform`, be sure to read the [PTransform Style
Guide]({{ site.baseurl }}/contribute/ptransform-style-guide/). The guide
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So demanding!

Maybe "The PTransform style guide contains additional information not included here such as...", "It is a useful starting point when writing new composite PTransforms"?

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modified


### Windowing functions
### 7.2. Beam windowing functions
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"Provided/Built-in window functions"?

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done


#### Single global window
#### 7.2.4. Single global window
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"The single global window"?

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done

default trigger generally requires the entire data set to be available before
processing, which is not possible with continuously updating data. To perform
aggregations on an unbounded `PCollection` that uses global windowing, you
should specify a non-default trigger for that `PCollection`.
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Maybe we should add (at some later point) a section on a custom window fn?

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opened JIRA


### <a name="setwindowingfunction"></a>Setting your PCollection's windowing function
### 7.3. Setting your PCollection's windowing function
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Can we condense the "How to construct a window fn" to the above section, and have this be just how to apply a WindowFn to a PCollection?

(Feel free to JIRA and do later)

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opened JIRA

```py
# The Beam SDK for Python does not support triggers.
```

##### <a name="default-trigger"></a>**Default Trigger**
#### 8.1.1. Default trigger
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The default trigger

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done

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Updated from feedback and resolved merge conflicts


##### 4.2.4.6. Combining values in a key-grouped collection
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done

* [Pre-written Beam transforms for Java]({{ site.baseurl }}/documentation/sdks/javadoc/{{ site.release_latest }}/index.html?org/apache/beam/sdk/transforms/package-summary.html)
* [Pre-written Beam transforms for Python]({{ site.baseurl }}/documentation/sdks/pydoc/{{ site.release_latest }}/apache_beam.transforms.html)

### An example of a composite transform
#### 4.6.1. Composite transform example
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done


When you create a pipeline, you often need to read data from some external source, such as a file in external data sink or a database. Likewise, you may want your pipeline to output its result data to a similar external data sink. Beam provides read and write transforms for a [number of common data storage types]({{site.baseurl }}/documentation/io/built-in/). If you want your pipeline to read from or write to a data storage format that isn't supported by the built-in transforms, you can [implement your own read and write transforms]({{site.baseurl }}/documentation/io/io-toc/).
When you create a new `PTransform`, be sure to read the [PTransform Style
Guide]({{ site.baseurl }}/contribute/ptransform-style-guide/). The guide
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modified


### Windowing functions
### 7.2. Beam windowing functions
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done


#### Single global window
#### 7.2.4. Single global window
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done

default trigger generally requires the entire data set to be available before
processing, which is not possible with continuously updating data. To perform
aggregations on an unbounded `PCollection` that uses global windowing, you
should specify a non-default trigger for that `PCollection`.
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opened JIRA

```py
# The Beam SDK for Python does not support triggers.
```

##### <a name="default-trigger"></a>**Default Trigger**
#### 8.1.1. Default trigger
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done


### <a name="setwindowingfunction"></a>Setting your PCollection's windowing function
### 7.3. Setting your PCollection's windowing function
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opened JIRA

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asfgit commented Sep 22, 2017

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/beam_PreCommit_Website_Stage/714/

Jenkins built the site at commit id c5d8da6 with Jekyll and staged it here. Happy reviewing.

Note that any previous site has been deleted. This staged site will be automatically deleted after its TTL expires. Push any commit to the pull request branch or re-trigger the build to get it staged again.

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tgroh commented Sep 22, 2017

LGTM

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tgroh commented Sep 22, 2017

@asfgit merge

asfgit pushed a commit that referenced this pull request Sep 22, 2017
@asfgit asfgit merged commit c5d8da6 into apache:asf-site Sep 22, 2017
@melap melap deleted the linecleanup branch September 25, 2017 21:21
robertwb pushed a commit to robertwb/incubator-beam that referenced this pull request Jun 5, 2018
robertwb pushed a commit to robertwb/incubator-beam that referenced this pull request Jun 5, 2018
melap pushed a commit to apache/beam that referenced this pull request Jun 20, 2018
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3 participants