[FLINK-17236][docs] Add Tutorials section overview

This closes apache#11826.

docs/concepts/index.md

@@ -1,8 +1,8 @@
 ---
-title: Concepts
+title: Concepts in Depth
 nav-id: concepts
-nav-pos: 2
-nav-title: '<i class="fa fa-map-o title appetizer" aria-hidden="true"></i> Concepts'
+nav-pos: 3
+nav-title: '<i class="fa fa-map-o title appetizer" aria-hidden="true"></i> Concepts in Depth'
 nav-parent_id: root
 nav-show_overview: true
 permalink: /concepts/index.html
@@ -27,20 +27,33 @@ specific language governing permissions and limitations
 under the License.
 -->
 
+The [Hands-on Tutorials]({{ site.baseurl }}{% link tutorials/index.md %}) explain the basic concepts
+of stateful and timely stream processing that underlie Flink's APIs, and provide examples of how
+these mechanisms are used in applications. Stateful stream processing is introduced in the context
+of [Data Pipelines & ETL]({{ site.baseurl }}{% link tutorials/etl.md %}#stateful-transformations)
+and is further developed in the section on [Fault Tolerance]({{ site.baseurl }}{% link
+tutorials/fault_tolerance.md %}). Timely stream processing is introduced in the section on
+[Streaming Analytics]({{ site.baseurl }}{% link tutorials/streaming_analytics.md %}).
+
+This _Concepts in Depth_ section provides a deeper understanding of how Flink's architecture and runtime 
+implement these concepts.
+
+## Flink's APIs
+
 Flink offers different levels of abstraction for developing streaming/batch applications.
 
 <img src="{{ site.baseurl }}/fig/levels_of_abstraction.svg" alt="Programming levels of abstraction" class="offset" width="80%" />
 
-  - The lowest level abstraction simply offers **stateful streaming**. It is
+  - The lowest level abstraction simply offers **stateful and timely stream processing**. It is
     embedded into the [DataStream API]({{ site.baseurl}}{% link
     dev/datastream_api.md %}) via the [Process Function]({{ site.baseurl }}{%
-    link dev/stream/operators/process_function.md %}). It allows users freely
-    process events from one or more streams, and use consistent fault tolerant
+    link dev/stream/operators/process_function.md %}). It allows users to freely
+    process events from one or more streams, and provides consistent, fault tolerant
     *state*. In addition, users can register event time and processing time
     callbacks, allowing programs to realize sophisticated computations.
 
-  - In practice, most applications would not need the above described low level
-    abstraction, but would instead program against the **Core APIs** like the
+  - In practice, many applications do not need the low-level
+    abstractions described above, and can instead program against the **Core APIs**: the
     [DataStream API]({{ site.baseurl }}{% link dev/datastream_api.md %})
     (bounded/unbounded streams) and the [DataSet API]({{ site.baseurl }}{% link
     dev/batch/index.md %}) (bounded data sets). These fluent APIs offer the
@@ -50,8 +63,8 @@ Flink offers different levels of abstraction for developing streaming/batch appl
     respective programming languages.
 
     The low level *Process Function* integrates with the *DataStream API*,
-    making it possible to go the lower level abstraction for certain operations
-    only. The *DataSet API* offers additional primitives on bounded data sets,
+    making it possible to use the lower-level abstraction on an as-needed basis. 
+    The *DataSet API* offers additional primitives on bounded data sets,
     like loops/iterations.
 
   - The **Table API** is a declarative DSL centered around *tables*, which may
@@ -77,7 +90,3 @@ Flink offers different levels of abstraction for developing streaming/batch appl
     }}{% link dev/table/index.md %}#sql) abstraction closely interacts with the
     Table API, and SQL queries can be executed over tables defined in the
     *Table API*.
-
-This _concepts_ section explains the basic concepts behind the different APIs,
-that is the concepts behind Flink as a stateful and timely stream processing
-system.

docs/concepts/index.zh.md

@@ -1,8 +1,8 @@
 ---
-title: 概念
+title: 概念透析
 nav-id: concepts
-nav-pos: 2
-nav-title: '<i class="fa fa-map-o title appetizer" aria-hidden="true"></i> 概念'
+nav-pos: 3
+nav-title: '<i class="fa fa-map-o title appetizer" aria-hidden="true"></i> 概念透析'
 nav-parent_id: root
 nav-show_overview: true
 permalink: /concepts/index.html
@@ -27,20 +27,33 @@ specific language governing permissions and limitations
 under the License.
 -->
 
+The [Hands-on Tutorials]({{ site.baseurl }}{% link tutorials/index.zh.md %}) explain the basic concepts
+of stateful and timely stream processing that underlie Flink's APIs, and provide examples of how
+these mechanisms are used in applications. Stateful stream processing is introduced in the context
+of [Data Pipelines & ETL]({{ site.baseurl }}{% link tutorials/etl.zh.md %}#stateful-transformations)
+and is further developed in the section on [Fault Tolerance]({{ site.baseurl }}{% link
+tutorials/fault_tolerance.zh.md %}). Timely stream processing is introduced in the section on
+[Streaming Analytics]({{ site.baseurl }}{% link tutorials/streaming_analytics.zh.md %}).
+
+This _Concepts in Depth_ section provides a deeper understanding of how Flink's architecture and runtime 
+implement these concepts.
+
+## Flink's APIs
+
 Flink offers different levels of abstraction for developing streaming/batch applications.
 
 <img src="{{ site.baseurl }}/fig/levels_of_abstraction.svg" alt="Programming levels of abstraction" class="offset" width="80%" />
 
-  - The lowest level abstraction simply offers **stateful streaming**. It is
+  - The lowest level abstraction simply offers **stateful and timely stream processing**. It is
     embedded into the [DataStream API]({{ site.baseurl}}{% link
     dev/datastream_api.zh.md %}) via the [Process Function]({{ site.baseurl }}{%
-    link dev/stream/operators/process_function.zh.md %}). It allows users freely
-    process events from one or more streams, and use consistent fault tolerant
+    link dev/stream/operators/process_function.zh.md %}). It allows users to freely
+    process events from one or more streams, and provides consistent, fault tolerant
     *state*. In addition, users can register event time and processing time
     callbacks, allowing programs to realize sophisticated computations.
 
-  - In practice, most applications would not need the above described low level
-    abstraction, but would instead program against the **Core APIs** like the
+  - In practice, many applications do not need the low-level
+    abstractions described above, and can instead program against the **Core APIs**: the
     [DataStream API]({{ site.baseurl }}{% link dev/datastream_api.zh.md %})
     (bounded/unbounded streams) and the [DataSet API]({{ site.baseurl }}{% link
     dev/batch/index.zh.md %}) (bounded data sets). These fluent APIs offer the
@@ -50,8 +63,8 @@ Flink offers different levels of abstraction for developing streaming/batch appl
     respective programming languages.
 
     The low level *Process Function* integrates with the *DataStream API*,
-    making it possible to go the lower level abstraction for certain operations
-    only. The *DataSet API* offers additional primitives on bounded data sets,
+    making it possible to use the lower-level abstraction on an as-needed basis. 
+    The *DataSet API* offers additional primitives on bounded data sets,
     like loops/iterations.
 
   - The **Table API** is a declarative DSL centered around *tables*, which may
@@ -63,12 +76,12 @@ Flink offers different levels of abstraction for developing streaming/batch appl
     programs declaratively define *what logical operation should be done*
     rather than specifying exactly *how the code for the operation looks*.
     Though the Table API is extensible by various types of user-defined
-    functions, it is less expressive than the *Core APIs*, but more concise to
+    functions, it is less expressive than the *Core APIs*, and more concise to
     use (less code to write).  In addition, Table API programs also go through
     an optimizer that applies optimization rules before execution.
 
     One can seamlessly convert between tables and *DataStream*/*DataSet*,
-    allowing programs to mix *Table API* and with the *DataStream* and
+    allowing programs to mix the *Table API* with the *DataStream* and
     *DataSet* APIs.
 
   - The highest level abstraction offered by Flink is **SQL**. This abstraction
@@ -77,7 +90,3 @@ Flink offers different levels of abstraction for developing streaming/batch appl
     }}{% link dev/table/index.zh.md %}#sql) abstraction closely interacts with the
     Table API, and SQL queries can be executed over tables defined in the
     *Table API*.
-
-This _concepts_ section explains the basic concepts behind the different APIs,
-that is the concepts behind Flink as a stateful and timely stream processing
-system.