JingsongLi commented on code in PR #531:
URL: https://github.com/apache/flink-web/pull/531#discussion_r867605296
##########
downloads.md:
##########
@@ -162,6 +162,27 @@ This version is compatible with Apache Flink version {{
flink_kubernetes_operato
{% endfor %}
+Apache Flink® Table Store {{ site.FLINK_TABLE_STORE_VERSION_STABLE }} is the
latest stable release for the [Flink Table
Store](https://github.com/apache/flink-table-store).
+
+{% for flink_table_store_release in site.flink_table_store_releases %}
+
+## {{ flink_table_store_release.source_release.name }}
+
+<p>
+<a href="{{ flink_table_store_release.source_release.url }}" id="{{
flink_table_store_release.source_release.id }}">{{
flink_table_store_release.source_release.name }} Source Release</a>
+(<a href="{{ flink_table_store_release.source_release.asc_url }}">asc</a>, <a
href="{{ flink_table_store_release.source_release.sha512_url }}">sha512</a>)
+</p>
+<p>
+<a href="{{ flink_table_store_release.binaries_release.url }}" id="{{
flink_table_store_release.binaries_release.id }}">{{
flink_table_store_release.binaries_release.name }} Binaries Release</a>
+(<a href="{{ flink_table_store_release.binaries_release.asc_url }}">asc</a>,
<a href="{{ flink_table_store_release.binaries_release.sha1_url }}">sha1</a>)
+</p>
+
+This version is compatible with Apache Flink version {{
flink_table_store_release.source_release.flink_version }}.
Review Comment:
Just one version
##########
_posts/2022-05-01-release-table-store-0.1.0.md:
##########
@@ -0,0 +1,110 @@
+---
+layout: post
+title: "Apache Flink Table Store 0.1.0 Release Announcement"
+subtitle: "Unified streaming and batch store for building dynamic tables on
Apache Flink."
+date: 2022-05-01T08:00:00.000Z
+categories: news
+authors:
+- Jingsong Lee:
+ name: "Jingsong Lee"
+
+---
+
+The Apache Flink community is pleased to announce the preview release of the
+[Apache Flink Table Store](https://github.com/apache/flink-table-store)
(0.1.0).
+
+Flink Table Store is a unified streaming and batch store for building dynamic
tables
+on Apache Flink. It uses a full Log-Structured Merge-Tree (LSM) structure for
high speed
+and a large amount of data update & query capability.
+
+Please check out the full
[documentation]({{site.DOCS_BASE_URL}}flink-table-store-docs-release-0.1/) for
detailed information and user guides.
+
+Note: Flink Table Store is still in beta status and undergoing rapid
development,
+we do not recommend that you use it directly in a production environment.
+
+## What is Flink Table Store
+
+Open [Flink official website](https://flink.apache.org/), you can see the
following line:
+`Apache Flink - Stateful Computations over Data Streams.` Flink focuses on
distributed computing,
+which brings real-time big data computing. Users need to combine Flink with
some kind of external storage.
+
+The message queue will be used in both source & intermediate stages in
streaming pipeline, to guarantee the
+latency stay within seconds. There will also be a real-time OLAP system
receiving processed data in streaming
+fashion and serving user’s ad-hoc queries.
+
+Everything works fine as long as users only care about the aggregated results.
But when users start to care
+about the intermediate data, they will immediately hit a blocker: Intermediate
kafka tables are not queryable.
+
+Therefore, users use multiple systems. Writing to a lake store like Apache
Hudi, Apache Iceberg while writing to Queue,
+the lake store keeps historical data at a lower cost.
+
+There are two main issues with doing this:
+- High understanding bar for users: It’s also not easy for users to understand
all the SQL connectors,
+ learn the capabilities and restrictions for each of those. Users may also
want to play around with
+ streaming & batch unification, but don't really know how, given the
connectors are most of the time different
+ in batch and streaming use cases.
+- Increasing architecture complexity: It’s hard to choose the most suited
external systems when the requirements
+ include streaming pipelines, offline batch jobs, ad-hoc queries. Multiple
systems will increase the operation
+ and maintenance complexity. Users at least need to coordinate between the
queue system and file system of each
+ table, which is error-prone.
+
+The Flink Table Store aims to provide a unified storage abstraction:
+- Table Store provides storage of historical data while providing queue
abstraction.
+- Table Store provides competitive historical storage with lake storage
capability, using LSM file structure
+ to store data on DFS, providing real-time updates and queries at a lower
cost.
Review Comment:
I will add cloud storage
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