[beam-site] 01/02: Add 2017 look back blog post

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commit 64b8b9d60cbe4f95c1a5bbf7f66b0499b286f5bd
Author: Jean-Baptiste Onofré <jb...@apache.org>
AuthorDate: Wed Jan 10 16:39:49 2018 +0100

    Add 2017 look back blog post
---
 src/_data/authors.yml                       |   8 ++
 src/_posts/2018-01-09-beam-a-look-back.md   | 132 ++++++++++++++++++++++++++++
 src/images/blog/2017-look-back/timeline.png | Bin 0 -> 12454 bytes
 3 files changed, 140 insertions(+)

diff --git a/src/_data/authors.yml b/src/_data/authors.yml
index d8cd836..0980cb5 100644
--- a/src/_data/authors.yml
+++ b/src/_data/authors.yml
@@ -47,3 +47,11 @@ jkff:
     name: Eugene Kirpichov
     email: ekirpichov@gmail.com
     twitter:
+jbonofre:
+    name: Jean-Baptiste Onofré
+    email: jbonofre@apache.org
+    twitter: jbonofre
+ianand:
+    name: Anand Iyer
+    email: ianand@google.com
+    twitter:
diff --git a/src/_posts/2018-01-09-beam-a-look-back.md b/src/_posts/2018-01-09-beam-a-look-back.md
new file mode 100644
index 0000000..d7643dc
--- /dev/null
+++ b/src/_posts/2018-01-09-beam-a-look-back.md
@@ -0,0 +1,132 @@
+---
+layout: post
+title:  "Apache Beam: A Look Back at 2017"
+date:   2018-01-09 00:00:01 -0800
+excerpt_separator: <!--more-->
+categories: blog
+authors:
+  - ianand
+  - jbonofre
+---
+
+On January 10, 2017, Apache Beam got [promoted]({{ site.baseurl }}/blog/2017/01/10/beam-graduates.html)
+as a Top-Level Apache Software Foundation project. It was an important milestone
+that validated the value of the project, legitimacy of its community, and
+heralded its growing adoption. In the past year, Apache Beam has been on a
+phenomenal growth trajectory, with significant growth in its community and
+feature set. Let us walk you through some of the notable achievements.
+
+<!--more-->
+
+## Use cases
+
+First, lets take a glimpse at how Beam was used in 2017. Apache Beam being a
+unified framework for batch and stream processing, enables a very wide spectrum
+of diverse use cases. Here are some use cases that exemplify the versatility of
+Beam.
+
+<img class="center-block"
+     src="{{ site.baseurl }}/images/blog/2017-look-back/timeline.png"
+     alt="Use Cases"
+     width="600">
+
+## Community growth
+
+In 2017, Apache Beam had 174 contributors worldwide, from many different
+organizations. As an Apache project, we are proud to count 18 PMC members and
+31 committers. The community had 7 releases in 2017, each bringing a rich set of
+new features and fixes.
+
+The most obvious and encouraging sign of the growth of Apache Beam’s community,
+and validation of its core value proposition of portability, is the addition of
+significant new [runners]({{ site.baseurl }}/documentation/runners/capability-matrix/)
+(i.e. execution engines). We entered 2017 with Apache Flink, Apache Spark 1.x,
+Google Cloud Dataflow, Apache Apex, and Apache Gearpump. In 2017, the following
+new and updated runners were developed:
+
+ - Apache Spark 2.x update
+ - [IBM Streams runner](https://www.ibm.com/blogs/bluemix/2017/10/streaming-analytics-updates-ibm-streams-runner-apache-beam-2-0/)
+ - MapReduce runner
+ - [JStorm runner](http://jstorm.io/)
+
+In addition to runners, Beam added new IO connectors, some notable ones being
+the Cassandra, MQTT, AMQP, HBase/HCatalog, JDBC, Solr, Tika, Redis, and
+ElasticSearch connectors. Beam’s IO connectors make it possible to read from or
+write to data sources/sinks even when they are not natively supported by the
+underlying execution engine. Beam also provides fully pluggable filesystem
+support, allowing us to support and extend our coverage to HDFS, S3, Azure
+Storage, and Google Storage. We continue to add new IO connectors and
+filesystems to extend the Beam use cases.
+
+A particularly telling sign of the maturity of an open source community is when
+it is able to collaborate with multiple other open source communities, and
+mutually improve the state of the art. Over the past few months, the Beam,
+Calcite, and Flink communities have come together to define a robust [spec](https://docs.google.com/document/d/1wrla8mF_mmq-NW9sdJHYVgMyZsgCmHumJJ5f5WUzTiM/edit)
+for Streaming SQL, with engineers from over four organizations contributing to
+it. If, like us, you are excited by the prospect of improving the state of
+streaming SQL, please join us!
+
+In addition to SQL, new XML and JSON based declarative DSLs are also in PoC.
+
+## Continued innovation
+
+Innovation is important to the success on any open source project, and Beam has
+a rich history of bringing innovative new ideas to the open source community.
+Apache Beam was the first to introduce some seminal concepts in the world of
+big-data processing:
+
+ - Unified batch and streaming SDK that enables users to author big-data jobs
+   without having to learn multiple disparate SDKs/APIs.
+ - Cross-Engine Portability: Giving enterprises the confidence that workloads
+   authored today will not have to be re-written when open source engines become
+   outdated and are supplanted by newer ones.
+ - [Semantics](https://www.oreilly.com/ideas/the-world-beyond-batch-streaming-101)
+   essential for reasoning about unbounded unordered data, and achieving
+   consistent and correct output from a streaming job.
+
+In 2017, the pace of innovation continued. The following capabilities were
+introduced:
+
+ - Cross-Language Portability framework, and a [Go](https://golang.org/) SDK
+   developed with it.
+ - Dynamically Shardable IO (SplittableDoFn)
+ - Support for schemas in PCollection, allowing us to extend the runner
+   capabilities.
+ - Extensions addressing new use cases such as machine learning, and new data
+   formats.
+
+## Areas of improvement
+
+Any retrospective view of a project is incomplete without an honest assessment
+of areas of improvement. Two aspects stand out:
+
+ - Helping runners showcase their individual strengths. After all, portability
+   does not imply homogeneity. Different runners have different areas in which
+   they excel, and we need to do a better job of helping them highlight their
+   strengths.
+ - Based on the previous point, helping customers make a more informed decision
+   when they select a runner or migrate from one to another.
+
+In 2018, we aim to take proactive steps to improve the above aspects.
+
+## Ethos of the project and its community
+
+The world of batch and stream big-data processing today is reminiscent of the
+[Tower of Babel](https://en.wikipedia.org/wiki/Tower_of_Babel) parable: a
+slowdown of progress because different communities spoke different languages.
+Similarly, today there are multiple disparate big-data SDKs/APIs, each with
+their own distinct terminology to describe similar concepts. The side effect is
+user confusion and slower adoption.
+
+The Apache Beam project aims to provide an industry standard portable SDK that
+will:
+
+ - Benefit users by providing ***innovation with stability***: The separation of
+   SDK and engine enables healthy competition between runners, without requiring
+   users to constantly learn new SDKs/APIs and rewrite their workloads to
+   benefit from new innovation.
+ - Benefit big-data engines by ***growing the pie for everyone***: Making it
+   easier for users to author, maintain, upgrade and migrate their big-data
+   workloads will lead to significant growth in the number of production
+   big-data deployments.
+
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