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jiayu pushed a commit to branch flink-docs
in repository https://gitbox.apache.org/repos/asf/incubator-sedona.git
The following commit(s) were added to refs/heads/flink-docs by this push:
new 9f84f83 Finish all but Flink tutorial
9f84f83 is described below
commit 9f84f83ad40a6ac864b7ecaef91bfb2431f448b0
Author: Jia Yu <[email protected]>
AuthorDate: Sat Mar 5 23:43:31 2022 -0800
Finish all but Flink tutorial
---
docs/api/flink/Constructor.md | 69 +++++++++
docs/api/flink/Function.md | 102 +++++++++++++
docs/api/flink/Overview.md | 12 ++
docs/api/flink/Predicate.md | 29 ++++
docs/setup/flink/install-scala.md | 13 ++
docs/setup/flink/modules.md | 15 ++
docs/setup/flink/platform.md | 7 +
docs/setup/maven-coordinates.md | 294 +++++++++++++++++++++++---------------
docs/setup/modules.md | 16 +++
docs/setup/overview.md | 40 +++---
docs/setup/platform.md | 2 +-
docs/tutorial/flink/sql.md | 283 ++++++++++++++++++++++++++++++++++++
mkdocs.yml | 120 +++++++++-------
13 files changed, 815 insertions(+), 187 deletions(-)
diff --git a/docs/api/flink/Constructor.md b/docs/api/flink/Constructor.md
new file mode 100644
index 0000000..ba25656
--- /dev/null
+++ b/docs/api/flink/Constructor.md
@@ -0,0 +1,69 @@
+## ST_GeomFromWKT
+
+Introduction: Construct a Geometry from Wkt
+
+Format:
+`ST_GeomFromWKT (Wkt:string)`
+
+Since: `v1.2.0`
+
+SQL example:
+```SQL
+SELECT ST_GeomFromWKT('POINT(40.7128 -74.0060)') AS geometry
+```
+
+## ST_GeomFromWKB
+
+Introduction: Construct a Geometry from WKB string
+
+Format:
+`ST_GeomFromWKB (Wkb:string)`
+
+Since: `v1.2.0`
+
+SQL example:
+```SQL
+SELECT ST_GeomFromWKB(polygontable._c0) AS polygonshape
+FROM polygontable
+```
+
+## ST_PointFromText
+
+Introduction: Construct a Point from Text, delimited by Delimiter
+
+Format: `ST_PointFromText (Text:string, Delimiter:char)`
+
+Since: `v1.2.0`
+
+SQL example:
+```SQL
+SELECT ST_PointFromText('40.7128,-74.0060', ',') AS pointshape
+```
+
+## ST_PolygonFromText
+
+Introduction: Construct a Polygon from Text, delimited by Delimiter. Path must
be closed
+
+Format: `ST_PolygonFromText (Text:string, Delimiter:char)`
+
+Since: `v1.0.0`
+
+SQL example:
+```SQL
+SELECT
ST_PolygonFromText('-74.0428197,40.6867969,-74.0421975,40.6921336,-74.0508020,40.6912794,-74.0428197,40.6867969',
',') AS polygonshape
+```
+
+## ST_PolygonFromEnvelope
+
+Introduction: Construct a Polygon from MinX, MinY, MaxX, MaxY.
+
+Format: `ST_PolygonFromEnvelope (MinX:decimal, MinY:decimal, MaxX:decimal,
MaxY:decimal)`
+
+Since: `v1.0.0`
+
+SQL example:
+```SQL
+SELECT *
+FROM pointdf
+WHERE ST_Contains(ST_PolygonFromEnvelope(1.0,100.0,1000.0,1100.0),
pointdf.pointshape)
+```
diff --git a/docs/api/flink/Function.md b/docs/api/flink/Function.md
new file mode 100644
index 0000000..c559abf
--- /dev/null
+++ b/docs/api/flink/Function.md
@@ -0,0 +1,102 @@
+## ST_Distance
+
+Introduction: Return the Euclidean distance between A and B
+
+Format: `ST_Distance (A:geometry, B:geometry)`
+
+Since: `v1.2.0`
+
+Spark SQL example:
+```SQL
+SELECT ST_Distance(polygondf.countyshape, polygondf.countyshape)
+FROM polygondf
+```
+
+## ST_Transform
+
+Introduction:
+
+Transform the Spatial Reference System / Coordinate Reference System of A,
from SourceCRS to TargetCRS
+
+!!!note
+ By default, this function uses lat/lon order. You can use
==ST_FlipCoordinates== to swap X and Y.
+
+!!!note
+ If ==ST_Transform== throws an Exception called "Bursa wolf parameters
required", you need to disable the error notification in ST_Transform. You can
append a boolean value at the end.
+
+Format: `ST_Transform (A:geometry, SourceCRS:string, TargetCRS:string
,[Optional] DisableError)`
+
+Since: `v1.2.0`
+
+Spark SQL example (simple):
+```SQL
+SELECT ST_Transform(polygondf.countyshape, 'epsg:4326','epsg:3857')
+FROM polygondf
+```
+
+Spark SQL example (with optional parameters):
+```SQL
+SELECT ST_Transform(polygondf.countyshape, 'epsg:4326','epsg:3857', false)
+FROM polygondf
+```
+
+!!!note
+ The detailed EPSG information can be searched on
[EPSG.io](https://epsg.io/).
+
+## ST_Buffer
+
+Introduction: Returns a geometry/geography that represents all points whose
distance from this Geometry/geography is less than or equal to distance.
+
+Format: `ST_Buffer (A:geometry, buffer: Double)`
+
+Since: `v1.2.0`
+
+Spark SQL example:
+```SQL
+SELECT ST_Buffer(polygondf.countyshape, 1)
+FROM polygondf
+```
+
+## ST_FlipCoordinates
+
+Introduction: Returns a version of the given geometry with X and Y axis
flipped.
+
+Format: `ST_FlipCoordinates(A:geometry)`
+
+Since: `v1.2.0`
+
+Spark SQL example:
+```SQL
+SELECT ST_FlipCoordinates(df.geometry)
+FROM df
+```
+
+Input: `POINT (1 2)`
+
+Output: `POINT (2 1)`
+
+## ST_GeoHash
+
+Introduction: Returns GeoHash of the geometry with given precision
+
+Format: `ST_GeoHash(geom: geometry, precision: int)`
+
+Since: `v1.2.0`
+
+Example:
+
+Query:
+
+```SQL
+SELECT ST_GeoHash(ST_GeomFromText('POINT(21.427834 52.042576573)'), 5) AS
geohash
+```
+
+Result:
+
+```
++-----------------------------+
+|geohash |
++-----------------------------+
+|u3r0p |
++-----------------------------+
+```
\ No newline at end of file
diff --git a/docs/api/flink/Overview.md b/docs/api/flink/Overview.md
new file mode 100644
index 0000000..56fb41d
--- /dev/null
+++ b/docs/api/flink/Overview.md
@@ -0,0 +1,12 @@
+# Introduction
+
+SedonaSQL supports SQL/MM Part3 Spatial SQL Standard. Please read the
programming guide: [Sedona with Flink application](../../tutorial/flink/sql.md).
+
+Sedona includes SQL operators as follows.
+
+* Constructor: Construct a Geometry given an input string or coordinates
+ * Example: ST_GeomFromWKT (string). Create a Geometry from a WKT String.
+* Function: Execute a function on the given column or columns
+ * Example: ST_Distance (A, B). Given two Geometry A and B, return the
Euclidean distance of A and B.
+* Predicate: Execute a logic judgement on the given columns and return true or
false
+ * Example: ST_Contains (A, B). Check if A fully contains B. Return
"True" if yes, else return "False".
diff --git a/docs/api/flink/Predicate.md b/docs/api/flink/Predicate.md
new file mode 100644
index 0000000..4e4fce6
--- /dev/null
+++ b/docs/api/flink/Predicate.md
@@ -0,0 +1,29 @@
+## ST_Contains
+
+Introduction: Return true if A fully contains B
+
+Format: `ST_Contains (A:geometry, B:geometry)`
+
+Since: `v1.2.0`
+
+SQL example:
+```SQL
+SELECT *
+FROM pointdf
+WHERE ST_Contains(ST_PolygonFromEnvelope(1.0,100.0,1000.0,1100.0),
pointdf.arealandmark)
+```
+
+## ST_Intersects
+
+Introduction: Return true if A intersects B
+
+Format: `ST_Intersects (A:geometry, B:geometry)`
+
+Since: `v1.2.0`
+
+SQL example:
+```SQL
+SELECT *
+FROM pointdf
+WHERE ST_Intersects(ST_PolygonFromEnvelope(1.0,100.0,1000.0,1100.0),
pointdf.arealandmark)
+```
\ No newline at end of file
diff --git a/docs/setup/flink/install-scala.md
b/docs/setup/flink/install-scala.md
new file mode 100644
index 0000000..8e7af1c
--- /dev/null
+++ b/docs/setup/flink/install-scala.md
@@ -0,0 +1,13 @@
+Before starting the Sedona journey, you need to make sure your Apache Flink
cluster is ready.
+
+Then you can create a self-contained Scala / Java project. A self-contained
project allows you to create multiple Scala / Java files and write complex
logics in one place.
+
+To use Sedona in your self-contained Flink project, you just need to add
Sedona as a dependency in your POM.xml or build.sbt.
+
+1. To add Sedona as dependencies, please read [Sedona Maven Central
coordinates](maven-coordinates.md)
+2. Use Sedona Template project to start: [Sedona Template
Project](/tutorial/demo/)
+3. Compile your project using Maven. Make sure you obtain the fat jar which
packages all dependencies.
+4. Submit your compiled fat jar to Flink cluster. Make sure you are in the
root folder of Flink distribution. Then run the following command:
+```
+./bin/flink run /Path/To/YourJar.jar
+```
\ No newline at end of file
diff --git a/docs/setup/flink/modules.md b/docs/setup/flink/modules.md
new file mode 100644
index 0000000..ef7d371
--- /dev/null
+++ b/docs/setup/flink/modules.md
@@ -0,0 +1,15 @@
+# Sedona modules for Apache Flink
+
+| Name | Introduction|
+|---|---|
+|Core|Spatial query algorithms, data readers/writers|
+|SQL|Spatial SQL function implementation|
+|Flink|Spatial Table and DataStream implementation|
+
+## API availability
+
+| | **DataStream** | **Table** |
+|:----------:|:------------:|:-----------------:|
+| Scala/Java |✅|✅|
+| Python |no|no|
+| R |no|no|
\ No newline at end of file
diff --git a/docs/setup/flink/platform.md b/docs/setup/flink/platform.md
new file mode 100644
index 0000000..3c49901
--- /dev/null
+++ b/docs/setup/flink/platform.md
@@ -0,0 +1,7 @@
+Sedona Flink binary releases are compiled by Java 1.8 and Scala 2.12 and
tested in the following environments:
+
+=== "Sedona Scala/Java"
+
+ | | Flink 1.12 | Flink 1.13 | Flink 1.14 |
+ |:-----------:| :---------:|:---------:|:---------:|
+ | Scala 2.12 | ✅ | ✅ | ✅ |
\ No newline at end of file
diff --git a/docs/setup/maven-coordinates.md b/docs/setup/maven-coordinates.md
index e2e3762..92d23cc 100644
--- a/docs/setup/maven-coordinates.md
+++ b/docs/setup/maven-coordinates.md
@@ -1,68 +1,106 @@
# Maven Coordinates
-Sedona has four modules: `sedona-core, sedona-sql, sedona-viz,
sedona-python-adapter`. They have different packing policies. You will need to
use `sedona-python-adapter` for Scala, Java and Python API. ==You may also
need geotools-wrapper (see below)==. If you want to use SedonaViz, you will
include one more jar: `sedona-viz`.
+Sedona Spark has four modules: `sedona-core, sedona-sql, sedona-viz,
sedona-python-adapter`. `sedona-python-adapter` is a fat jar of `sedona-core,
sedona-sql` and python adapter code. If you want to use SedonaViz, you will
include one more jar: `sedona-viz`.
-## Use Sedona fat jars
+Sedona Flink has four modules :`sedona-core, sedona-sql,
sedona-python-adapter, sedona-flink`. `sedona-python-adapter` is a fat jar of
`sedona-core, sedona-sql`.
-=== "Spark 3.0 + Scala 2.12"
-
- ```xml
- <dependency>
- <groupId>org.apache.sedona</groupId>
- <artifactId>sedona-python-adapter-3.0_2.12</artifactId>
- <version>{{ sedona.current_version }}</version>
- </dependency>
- <dependency>
- <groupId>org.apache.sedona</groupId>
- <artifactId>sedona-viz-3.0_2.12</artifactId>
- <version>{{ sedona.current_version }}</version>
- </dependency>
- ```
-
-=== "Spark 2.4 + Scala 2.11"
-
- ```xml
- <dependency>
- <groupId>org.apache.sedona</groupId>
- <artifactId>sedona-python-adapter-2.4_2.11</artifactId>
- <version>{{ sedona.current_version }}</version>
- </dependency>
- <dependency>
- <groupId>org.apache.sedona</groupId>
- <artifactId>sedona-viz-2.4_2.11</artifactId>
- <version>{{ sedona.current_version }}</version>
- </dependency>
- ```
-
-=== "Spark 2.4 + Scala 2.12"
-
- ```xml
- <dependency>
- <groupId>org.apache.sedona</groupId>
- <artifactId>sedona-python-adapter-2.4_2.12</artifactId>
- <version>{{ sedona.current_version }}</version>
- </dependency>
- <dependency>
- <groupId>org.apache.sedona</groupId>
- <artifactId>sedona-viz-2.4_2.12</artifactId>
- <version>{{ sedona.current_version }}</version>
- </dependency>
- ```
-### GeoTools 24.0+
+## Use Sedona fat jars
-GeoTools library is required only if you want to use CRS transformation and
ShapefileReader. This wrapper library is a re-distriution of GeoTools official
jars. The only purpose of this library is to bring GeoTools jars from OSGEO
repository to Maven Central. This libary is under GNU Lesser General Public
License (LGPL) license so we cannot package it in Sedona official release.
+This is the most common way to use Sedona in your environment. Do not use
separate Sedona jars if you are not familar with Maven.
-```xml
-<!-- https://mvnrepository.com/artifact/org.datasyslab/geotools-wrapper -->
-<dependency>
- <groupId>org.datasyslab</groupId>
- <artifactId>geotools-wrapper</artifactId>
- <version>{{ sedona.current_geotools }}</version>
-</dependency>
-```
+The optional GeoTools library is required only if you want to use CRS
transformation and ShapefileReader. This wrapper library is a re-distriution of
GeoTools official jars. The only purpose of this library is to bring GeoTools
jars from OSGEO repository to Maven Central. This libary is under GNU Lesser
General Public License (LGPL) license so we cannot package it in Sedona
official release.
-### SernetCDF 0.1.0
+!!! abstract "Sedona with Apache Spark"
+
+ === "Spark 3.0+ and Scala 2.12"
+
+ ```xml
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-python-adapter-3.0_2.12</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-viz-3.0_2.12</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <!-- Optional:
https://mvnrepository.com/artifact/org.datasyslab/geotools-wrapper -->
+ <dependency>
+ <groupId>org.datasyslab</groupId>
+ <artifactId>geotools-wrapper</artifactId>
+ <version>{{ sedona.current_geotools }}</version>
+ </dependency>
+ ```
+
+ === "Spark 2.4 and Scala 2.11"
+
+ ```xml
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-python-adapter-2.4_2.11</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-viz-2.4_2.11</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <!-- Optional:
https://mvnrepository.com/artifact/org.datasyslab/geotools-wrapper -->
+ <dependency>
+ <groupId>org.datasyslab</groupId>
+ <artifactId>geotools-wrapper</artifactId>
+ <version>{{ sedona.current_geotools }}</version>
+ </dependency>
+ ```
+
+ === "Spark 2.4 and Scala 2.12"
+
+ ```xml
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-python-adapter-2.4_2.12</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-viz-2.4_2.12</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <!-- Optional:
https://mvnrepository.com/artifact/org.datasyslab/geotools-wrapper -->
+ <dependency>
+ <groupId>org.datasyslab</groupId>
+ <artifactId>geotools-wrapper</artifactId>
+ <version>{{ sedona.current_geotools }}</version>
+ </dependency>
+ ```
+
+!!! abstract "Sedona with Apache Flink"
+
+ === "Flink 2.12+ and Scala 2.12"
+
+ ```xml
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-python-adapter-3.0_2.12</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-flink_2.12</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <!-- Optional:
https://mvnrepository.com/artifact/org.datasyslab/geotools-wrapper -->
+ <dependency>
+ <groupId>org.datasyslab</groupId>
+ <artifactId>geotools-wrapper</artifactId>
+ <version>{{ sedona.current_geotools }}</version>
+ </dependency>
+ ```
+
+
+#### SernetCDF 0.1.0
For Scala / Java API, it is required only if you want to read HDF/NetCDF files.
@@ -83,65 +121,89 @@ Under Apache License 2.0.
==For Scala and Java users==, if by any chance you don't want to use an uber
jar that includes every dependency, you can use the following jars instead.
==Otherwise, please do not continue reading this section.==
-=== "Spark 3.0 + Scala 2.12"
-
- ```xml
- <dependency>
- <groupId>org.apache.sedona</groupId>
- <artifactId>sedona-core-3.0_2.12</artifactId>
- <version>{{ sedona.current_version }}</version>
- </dependency>
- <dependency>
- <groupId>org.apache.sedona</groupId>
- <artifactId>sedona-sql-3.0_2.12</artifactId>
- <version>{{ sedona.current_version }}</version>
- </dependency>
- <dependency>
- <groupId>org.apache.sedona</groupId>
- <artifactId>sedona-viz-3.0_2.12</artifactId>
- <version>{{ sedona.current_version }}</version>
- </dependency>
- ```
-
-=== "Spark 2.4 + Scala 2.11"
-
- ```xml
- <dependency>
- <groupId>org.apache.sedona</groupId>
- <artifactId>sedona-core-2.4_2.11</artifactId>
- <version>{{ sedona.current_version }}</version>
- </dependency>
- <dependency>
- <groupId>org.apache.sedona</groupId>
- <artifactId>sedona-sql-2.4_2.11</artifactId>
- <version>{{ sedona.current_version }}</version>
- </dependency>
- <dependency>
- <groupId>org.apache.sedona</groupId>
- <artifactId>sedona-viz-2.4_2.11</artifactId>
- <version>{{ sedona.current_version }}</version>
- </dependency>
- ```
-
-=== "Spark 2.4 + Scala 2.12"
-
- ```xml
- <dependency>
- <groupId>org.apache.sedona</groupId>
- <artifactId>sedona-core-2.4_2.12</artifactId>
- <version>{{ sedona.current_version }}</version>
- </dependency>
- <dependency>
- <groupId>org.apache.sedona</groupId>
- <artifactId>sedona-sql-2.4_2.12</artifactId>
- <version>{{ sedona.current_version }}</version>
- </dependency>
- <dependency>
- <groupId>org.apache.sedona</groupId>
- <artifactId>sedona-viz-2.4_2.12</artifactId>
- <version>{{ sedona.current_version }}</version>
- </dependency>
- ```
+!!! abstract "Sedona with Apache Spark"
+
+ === "Spark 3.0+ and Scala 2.12"
+
+ ```xml
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-core-3.0_2.12</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-sql-3.0_2.12</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-viz-3.0_2.12</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ ```
+
+ === "Spark 2.4 and Scala 2.11"
+
+ ```xml
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-core-2.4_2.11</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-sql-2.4_2.11</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-viz-2.4_2.11</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ ```
+
+ === "Spark 2.4 and Scala 2.12"
+
+ ```xml
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-core-2.4_2.12</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-sql-2.4_2.12</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-viz-2.4_2.12</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ ```
+
+!!! abstract "Sedona with Apache Flink"
+
+ === "Flink 1.12+ and Scala 2.12"
+
+ ```xml
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-core-3.0_2.12</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-sql-3.0_2.12</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ <dependency>
+ <groupId>org.apache.sedona</groupId>
+ <artifactId>sedona-flink-3.0_2.12</artifactId>
+ <version>{{ sedona.current_version }}</version>
+ </dependency>
+ ```
### LocationTech JTS-core 1.18.0+
diff --git a/docs/setup/modules.md b/docs/setup/modules.md
new file mode 100644
index 0000000..82fd96d
--- /dev/null
+++ b/docs/setup/modules.md
@@ -0,0 +1,16 @@
+# Sedona modules for Apache Spark
+
+| Name | API | Introduction|
+|---|---|---|
+|Core | RDD | SpatialRDDs and Query Operators. |
+|SQL | SQL/DataFrame |SQL interfaces for Sedona core.|
+|Viz | RDD, SQL/DataFrame | Visualization for Spatial RDD and DataFrame|
+|Zeppelin | Apache Zeppelin | Plugin for Apache Zeppelin 0.8.1+|
+
+## API availability
+
+| | **Core/RDD** | **DataFrame/SQL** | **Viz RDD/SQL** |
+|:----------:|:------------:|:-----------------:|:---------------:|
+| Scala/Java |✅|✅|✅|
+| Python |✅|✅|SQL only|
+| R |✅|✅|✅|
\ No newline at end of file
diff --git a/docs/setup/overview.md b/docs/setup/overview.md
index 4121b6a..59a6208 100644
--- a/docs/setup/overview.md
+++ b/docs/setup/overview.md
@@ -1,33 +1,33 @@
-## Companies are using Sedona
+# Who are using Sedona?
-[<img
src="https://www.dataiku.com/static/img/partners/LOGO-Blue-DME-PNG-3.png";
width="200">](https://www.bluedme.com/)
-[<img
src="https://images.ukfast.co.uk/comms/news/businesscloud/photos/14-08-2018/gyana.jpg";
width="150">](https://www.gyana.co.uk/)
-[<img
src="https://149448277.v2.pressablecdn.com/wp-content/uploads/2021/03/guy-carpenter-logo-1.png";
width="130">](https://guycarp.com/)
+[<img
src="https://www.dataiku.com/static/img/partners/LOGO-Blue-DME-PNG-3.png";
width="100">](https://www.bluedme.com/)
+[<img
src="https://images.ukfast.co.uk/comms/news/businesscloud/photos/14-08-2018/gyana.jpg";
width="100">](https://www.gyana.co.uk/)
+[<img
src="https://149448277.v2.pressablecdn.com/wp-content/uploads/2021/03/guy-carpenter-logo-1.png";
width="80">](https://guycarp.com/) [<img
src="../../image/meituan-bike.png" width="170">](http://t8.pub) and more...
+|Download statistics| **Maven** | **PyPI** | **CRAN** |
+|:-------------:|:------------------:|:--------------:|:---------:|
+| Apache Sedona | 80k/month
|[](https://pepy.tech/project/apache-sedona)
[](https://pepy.tech/project/apache-sedona)|[!
[...]
+| Archived GeoSpark releases
|300k/month|[](https://pepy.tech/project/geospark)[](https://pepy.tech/project/geospark)|
|
-[<img src="../../image/meituan-bike.png" width="170">](http://t8.pub) and
more...
+# What can Sedona do?
-Please make a Pull Request to add yourself!
+## Distributed spatial datasets
+- [x] Spatial RDD on Spark
+- [x] Spatial DataFrame/SQL on Spark
+- [x] Spatial DataStream on Flink
+- [x] Spatial Table/SQL on Flink
-## Sedona modules
-
-| Name | API | Introduction|
-|---|---|---|
-|Core | RDD | SpatialRDDs and Query Operators. |
-|SQL | SQL/DataFrame |SQL interfaces for Sedona core.|
-|Viz | RDD, SQL/DataFrame | Visualization for Spatial RDD and DataFrame|
-|Zeppelin | Apache Zeppelin | Plugin for Apache Zeppelin 0.8.1+|
-
-## Features
-
-- [x] Spatial RDD
-- [x] Spatial DataFrame/SQL
+## Complex spatial objects
- [x] Vector geometries / trajectories
- [x] Raster images with Map Algebra
- [x] Various input formats: CSV, TSV, WKT, WKB, GeoJSON, Shapefile, GeoTIFF,
NetCDF/HDF
+
+## Distributed spatial queries
- [x] Spatial query: range query, range join query, distance join query, K
Nearest Neighbor query
- [x] Spatial index: R-Tree, Quad-Tree
+
+## Rich spatial analytics tools
- [x] Coordinate Reference System / Spatial Reference System Transformation
- [x] High resolution map generation: [Visualize Spatial
DataFrame/RDD](../../tutorial/viz)
- [x] Apache Zeppelin integration
-- [x] Support Scala, Java, Python, R
+- [x] Support Scala, Java, Python, R
\ No newline at end of file
diff --git a/docs/setup/platform.md b/docs/setup/platform.md
index f3a5f00..ed60958 100644
--- a/docs/setup/platform.md
+++ b/docs/setup/platform.md
@@ -22,6 +22,6 @@ Sedona binary releases are compiled by Java 1.8 and Scala
2.11/2.12 and tested i
|:-----------:| :---------:|:---------:|:---------:|:---------:|
| Scala 2.11 | ✅ | not tested | not tested | not tested |
| Scala 2.12 | not tested | ✅ | ✅ | ✅ | ✅ |
-
+
!!!warning
Sedona Scala/Java/Python/R also work with Spark 2.3, Python 3.6 but we
have no plan to officially support it.
\ No newline at end of file
diff --git a/docs/tutorial/flink/sql.md b/docs/tutorial/flink/sql.md
new file mode 100644
index 0000000..2765b9f
--- /dev/null
+++ b/docs/tutorial/flink/sql.md
@@ -0,0 +1,283 @@
+The page outlines the steps to manage spatial data using SedonaSQL. ==The
example code is written in Scala but also works for Java==.
+
+SedonaSQL supports SQL/MM Part3 Spatial SQL Standard. It includes four kinds
of SQL operators as follows. All these operators can be directly called through:
+```Scala
+var myDataFrame = sparkSession.sql("YOUR_SQL")
+```
+
+Detailed SedonaSQL APIs are available here: [SedonaSQL
API](../api/sql/Overview.md)
+
+## Set up dependencies
+
+1. Read [Sedona Maven Central coordinates](../setup/maven-coordinates.md)
+2. Select ==the minimum dependencies==: Add [Apache Spark
core](https://mvnrepository.com/artifact/org.apache.spark/spark-core_2.11),
[Apache
SparkSQL](https://mvnrepository.com/artifact/org.apache.spark/spark-sql),
Sedona-core and Sedona-SQL
+3. Add the dependencies in build.sbt or pom.xml.
+
+!!!note
+ To enjoy the full functions of Sedona, we suggest you include ==the
full dependencies==: [Apache Spark
core](https://mvnrepository.com/artifact/org.apache.spark/spark-core_2.11),
[Apache
SparkSQL](https://mvnrepository.com/artifact/org.apache.spark/spark-sql),
Sedona-core, Sedona-SQL, Sedona-Viz. Please see [SQL example
project](/tutorial/demo/)
+
+
+## Initiate SparkSession
+Use the following code to initiate your SparkSession at the beginning:
+```Scala
+var sparkSession = SparkSession.builder()
+.master("local[*]") // Delete this if run in cluster mode
+.appName("readTestScala") // Change this to a proper name
+// Enable Sedona custom Kryo serializer
+.config("spark.serializer", classOf[KryoSerializer].getName) //
org.apache.spark.serializer.KryoSerializer
+.config("spark.kryo.registrator", classOf[SedonaKryoRegistrator].getName)
+.getOrCreate() // org.apache.sedona.core.serde.SedonaKryoRegistrator
+```
+
+!!!warning
+ Sedona has a suite of well-written geometry and index serializers.
Forgetting to enable these serializers will lead to high memory consumption.
+
+If you add ==the Sedona full dependencies== as suggested above, please use the
following two lines to enable Sedona Kryo serializer instead:
+```Scala
+.config("spark.serializer", classOf[KryoSerializer].getName) //
org.apache.spark.serializer.KryoSerializer
+.config("spark.kryo.registrator", classOf[SedonaVizKryoRegistrator].getName)
// org.apache.sedona.viz.core.Serde.SedonaVizKryoRegistrator
+```
+
+## Register SedonaSQL
+
+Add the following line after your SparkSession declaration
+
+```Scala
+SedonaSQLRegistrator.registerAll(sparkSession)
+```
+
+This function will register Sedona User Defined Type, User Defined Function
and optimized join query strategy.
+
+You can also register everything by passing `--conf
spark.sql.extensions=org.apache.sedona.sql.SedonaSqlExtensions` to
`spark-submit` or `spark-shell`.
+
+## Load data from files
+
+Assume we have a WKT file, namely `usa-county.tsv`, at Path
`/Download/usa-county.tsv` as follows:
+
+```
+POLYGON (..., ...) Cuming County
+POLYGON (..., ...) Wahkiakum County
+POLYGON (..., ...) De Baca County
+POLYGON (..., ...) Lancaster County
+```
+The file may have many other columns.
+
+Use the following code to load the data and create a raw DataFrame:
+
+```Scala
+var rawDf = sparkSession.read.format("csv").option("delimiter",
"\t").option("header", "false").load("/Download/usa-county.tsv")
+rawDf.createOrReplaceTempView("rawdf")
+rawDf.show()
+```
+
+The output will be like this:
+
+```
+| _c0|_c1|_c2| _c3| _c4| _c5|
_c6|_c7|_c8| _c9|_c10| _c11|_c12|_c13| _c14| _c15| _c16|
_c17|
++--------------------+---+---+--------+-----+-----------+--------------------+---+---+-----+----+-----+----+----+----------+--------+-----------+------------+
+|POLYGON ((-97.019...| 31|039|00835841|31039| Cuming| Cuming County|
06| H1|G4020|null| null|null| A|1477895811|10447360|+41.9158651|-096.7885168|
+|POLYGON ((-123.43...| 53|069|01513275|53069| Wahkiakum| Wahkiakum County|
06| H1|G4020|null| null|null| A| 682138871|61658258|+46.2946377|-123.4244583|
+|POLYGON ((-104.56...| 35|011|00933054|35011| De Baca| De Baca County|
06| H1|G4020|null| null|null| A|6015539696|29159492|+34.3592729|-104.3686961|
+|POLYGON ((-96.910...| 31|109|00835876|31109| Lancaster| Lancaster County|
06| H1|G4020| 339|30700|null| A|2169240202|22877180|+40.7835474|-096.6886584|
+```
+
+## Create a Geometry type column
+
+All geometrical operations in SedonaSQL are on Geometry type objects.
Therefore, before any kind of queries, you need to create a Geometry type
column on a DataFrame.
+
+
+```Scala
+var spatialDf = sparkSession.sql(
+ """
+ |SELECT ST_GeomFromWKT(_c0) AS countyshape, _c1, _c2
+ |FROM rawdf
+ """.stripMargin)
+spatialDf.createOrReplaceTempView("spatialdf")
+spatialDf.show()
+```
+
+You can select many other attributes to compose this `spatialdDf`. The output
will be something like this:
+
+```
+| countyshape|_c1|_c2| _c3| _c4| _c5|
_c6|_c7|_c8| _c9|_c10| _c11|_c12|_c13| _c14| _c15| _c16|
_c17|
++--------------------+---+---+--------+-----+-----------+--------------------+---+---+-----+----+-----+----+----+----------+--------+-----------+------------+
+|POLYGON ((-97.019...| 31|039|00835841|31039| Cuming| Cuming County|
06| H1|G4020|null| null|null| A|1477895811|10447360|+41.9158651|-096.7885168|
+|POLYGON ((-123.43...| 53|069|01513275|53069| Wahkiakum| Wahkiakum County|
06| H1|G4020|null| null|null| A| 682138871|61658258|+46.2946377|-123.4244583|
+|POLYGON ((-104.56...| 35|011|00933054|35011| De Baca| De Baca County|
06| H1|G4020|null| null|null| A|6015539696|29159492|+34.3592729|-104.3686961|
+|POLYGON ((-96.910...| 31|109|00835876|31109| Lancaster| Lancaster County|
06| H1|G4020| 339|30700|null| A|2169240202|22877180|+40.7835474|-096.6886584|
+```
+
+Although it looks same with the input, but actually the type of column
countyshape has been changed to ==Geometry== type.
+
+To verify this, use the following code to print the schema of the DataFrame:
+
+```Scala
+spatialDf.printSchema()
+```
+
+The output will be like this:
+
+```
+root
+ |-- countyshape: geometry (nullable = false)
+ |-- _c1: string (nullable = true)
+ |-- _c2: string (nullable = true)
+ |-- _c3: string (nullable = true)
+ |-- _c4: string (nullable = true)
+ |-- _c5: string (nullable = true)
+ |-- _c6: string (nullable = true)
+ |-- _c7: string (nullable = true)
+```
+
+!!!note
+ SedonaSQL provides lots of functions to create a Geometry column,
please read [SedonaSQL constructor API](../api/sql/Constructor.md).
+
+## Load Shapefile and GeoJSON
+
+Shapefile and GeoJSON must be loaded by SpatialRDD and converted to DataFrame
using Adapter. Please read [Load
SpatialRDD](../rdd/#create-a-generic-spatialrdd) and [DataFrame <->
RDD](#convert-between-dataframe-and-spatialrdd).
+
+
+## Transform the Coordinate Reference System
+
+Sedona doesn't control the coordinate unit (degree-based or meter-based) of
all geometries in a Geometry column. The unit of all related distances in
SedonaSQL is same as the unit of all geometries in a Geometry column.
+
+To convert Coordinate Reference System of the Geometry column created before,
use the following code:
+
+```Scala
+spatialDf = sparkSession.sql(
+ """
+ |SELECT ST_Transform(countyshape, "epsg:4326", "epsg:3857") AS
newcountyshape, _c1, _c2, _c3, _c4, _c5, _c6, _c7
+ |FROM spatialdf
+ """.stripMargin)
+spatialDf.createOrReplaceTempView("spatialdf")
+spatialDf.show()
+```
+
+The first EPSG code EPSG:4326 in `ST_Transform` is the source CRS of the
geometries. It is WGS84, the most common degree-based CRS.
+
+The second EPSG code EPSG:3857 in `ST_Transform` is the target CRS of the
geometries. It is the most common meter-based CRS.
+
+This `ST_Transform` transform the CRS of these geomtries from EPSG:4326 to
EPSG:3857. The details CRS information can be found on
[EPSG.io](https://epsg.io/.)
+
+The coordinates of polygons have been changed. The output will be like this:
+
+```
++--------------------+---+---+--------+-----+-----------+--------------------+---+
+| newcountyshape|_c1|_c2| _c3| _c4| _c5|
_c6|_c7|
++--------------------+---+---+--------+-----+-----------+--------------------+---+
+|POLYGON ((-108001...| 31|039|00835841|31039| Cuming| Cuming County|
06|
+|POLYGON ((-137408...| 53|069|01513275|53069| Wahkiakum| Wahkiakum County|
06|
+|POLYGON ((-116403...| 35|011|00933054|35011| De Baca| De Baca County|
06|
+|POLYGON ((-107880...| 31|109|00835876|31109| Lancaster| Lancaster County|
06|
+
+```
+
+
+## Run spatial queries
+
+After creating a Geometry type column, you are able to run spatial queries.
+
+### Range query
+
+Use ==ST_Contains==, ==ST_Intersects==, ==ST_Within== to run a range query
over a single column.
+
+The following example finds all counties that are within the given polygon:
+
+```Scala
+spatialDf = sparkSession.sql(
+ """
+ |SELECT *
+ |FROM spatialdf
+ |WHERE ST_Contains (ST_PolygonFromEnvelope(1.0,100.0,1000.0,1100.0),
newcountyshape)
+ """.stripMargin)
+spatialDf.createOrReplaceTempView("spatialdf")
+spatialDf.show()
+```
+
+!!!note
+ Read [SedonaSQL constructor API](../api/sql/Constructor.md) to learn
how to create a Geometry type query window
+### KNN query
+
+Use ==ST_Distance== to calculate the distance and rank the distance.
+
+The following code returns the 5 nearest neighbor of the given polygon.
+
+```Scala
+spatialDf = sparkSession.sql(
+ """
+ |SELECT countyname,
ST_Distance(ST_PolygonFromEnvelope(1.0,100.0,1000.0,1100.0), newcountyshape) AS
distance
+ |FROM spatialdf
+ |ORDER BY distance DESC
+ |LIMIT 5
+ """.stripMargin)
+spatialDf.createOrReplaceTempView("spatialdf")
+spatialDf.show()
+```
+
+### Join query
+
+The details of a join query is available here [Join
query](../api/sql/Optimizer.md).
+
+### Other queries
+
+There are lots of other functions can be combined with these queries. Please
read [SedonaSQL functions](../api/sql/Function.md) and [SedonaSQL aggregate
functions](../api/sql/AggregateFunction.md).
+
+## Save to permanent storage
+
+To save a Spatial DataFrame to some permanent storage such as Hive tables and
HDFS, you can simply convert each geometry in the Geometry type column back to
a plain String and save the plain DataFrame to wherever you want.
+
+
+Use the following code to convert the Geometry column in a DataFrame back to a
WKT string column:
+```Scala
+var stringDf = sparkSession.sql(
+ """
+ |SELECT ST_AsText(countyshape)
+ |FROM polygondf
+ """.stripMargin)
+```
+
+!!!note
+ ST_AsGeoJSON is also available. We would like to invite you to
contribute more functions
+
+
+## Convert between DataFrame and SpatialRDD
+
+### DataFrame to SpatialRDD
+
+Use SedonaSQL DataFrame-RDD Adapter to convert a DataFrame to an SpatialRDD.
Please read [Adapter
Scaladoc](/api/javadoc/sql/org/apache/sedona/sql/utils/index.html)
+
+```Scala
+var spatialRDD = Adapter.toSpatialRdd(spatialDf, "usacounty")
+```
+
+"usacounty" is the name of the geometry column
+
+!!!warning
+ Only one Geometry type column is allowed per DataFrame.
+
+### SpatialRDD to DataFrame
+
+Use SedonaSQL DataFrame-RDD Adapter to convert a DataFrame to an SpatialRDD.
Please read [Adapter
Scaladoc](/api/javadoc/sql/org/apache/sedona/sql/utils/index.html)
+
+```Scala
+var spatialDf = Adapter.toDf(spatialRDD, sparkSession)
+```
+
+All other attributes such as price and age will be also brought to the
DataFrame as long as you specify ==carryOtherAttributes== (see [Read other
attributes in an SpatialRDD](../rdd#read-other-attributes-in-an-spatialrdd)).
+
+### SpatialPairRDD to DataFrame
+
+PairRDD is the result of a spatial join query or distance join query.
SedonaSQL DataFrame-RDD Adapter can convert the result to a DataFrame. But you
need to provide the name of other attributes.
+
+```Scala
+var joinResultDf = Adapter.toDf(joinResultPairRDD, Seq("left_attribute1",
"left_attribute2"), Seq("right_attribute1", "right_attribute2"), sparkSession)
+```
+
+or you can use the attribute names directly from the input RDD
+
+```Scala
+import scala.collection.JavaConversions._
+var joinResultDf = Adapter.toDf(joinResultPairRDD, leftRdd.fieldNames,
rightRdd.fieldNames, sparkSession)
+```
+
+All other attributes such as price and age will be also brought to the
DataFrame as long as you specify ==carryOtherAttributes== (see [Read other
attributes in an SpatialRDD](../rdd#read-other-attributes-in-an-spatialrdd)).
diff --git a/mkdocs.yml b/mkdocs.yml
index 0bc1eab..63f5534 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -1,64 +1,83 @@
site_name: Apache Sedona™ (incubating)
-site_description: Apache Sedona (incubating) is a cluster computing system for
processing large-scale spatial data. Sedona extends Apache Spark / SparkSQL
with a set of out-of-the-box Spatial Resilient Distributed Datasets /
SpatialSQL that efficiently load, process, and analyze large-scale spatial data
across machines.
+site_description: Apache Sedona (incubating) is a cluster computing system for
processing large-scale spatial data. Sedona extends Apache Spark and Apache
Flink with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL
that efficiently load, process, and analyze large-scale spatial data across
machines.
nav:
- Home: index.md
- Setup:
- Overview: setup/overview.md
- - Supported platforms: setup/platform.md
- - Maven Central coordinate: setup/maven-coordinates.md
- - Installation:
+ - Supported platforms:
+ - Sedona with Apache Spark:
+ - Modules: setup/modules.md
+ - Language wrappers: setup/platform.md
+ - Sedona with Apache Flink:
+ - Modules: setup/flink/modules.md
+ - Language wrappers: setup/flink/platform.md
+ - Maven Central coordinate: setup/maven-coordinates.md
+ - Install with Apache Spark:
- Install Sedona Scala/Java: setup/install-scala.md
- Install Sedona Python: setup/install-python.md
- Install Sedona R: setup/install-r.md
- Install Sedona-Zeppelin: setup/zeppelin.md
- Install on Databricks: setup/databricks.md
+ - Set up Spark cluser: setup/cluster.md
+ - Install with Apache Flink:
+ - Install Sedona Scala/Java: setup/flink/install-scala.md
- Release notes: setup/release-notes.md
- - Set up Spark cluser: setup/cluster.md
- Compile the code: setup/compile.md
- Publish the code: setup/publish.md
- Download: download.md
- Programming Guides:
- - Spatial RDD app:
- - Scala/Java: tutorial/rdd.md
- - Python: tutorial/core-python.md
- - R: tutorial/rdd-r.md
- - Spatial SQL app:
- - Scala/Java: tutorial/sql.md
- - Pure SQL: tutorial/sql-pure-sql.md
- - Python: tutorial/sql-python.md
- - R: tutorial/sql-r.md
- - Raster data - Map Algebra: tutorial/raster.md
- - Map visualization SQL app:
- - Scala/Java: tutorial/viz.md
- - Use Apache Zeppelin: tutorial/zeppelin.md
- - R: tutorial/viz-r.md
- - Gallery: tutorial/viz-gallery.md
+ - Sedona with Apache Spark:
+ - Spatial SQL app:
+ - Scala/Java: tutorial/sql.md
+ - Pure SQL: tutorial/sql-pure-sql.md
+ - Python: tutorial/sql-python.md
+ - R: tutorial/sql-r.md
+ - Raster data - Map Algebra: tutorial/raster.md
+ - Spatial RDD app:
+ - Scala/Java: tutorial/rdd.md
+ - Python: tutorial/core-python.md
+ - R: tutorial/rdd-r.md
+ - Map visualization SQL app:
+ - Scala/Java: tutorial/viz.md
+ - Use Apache Zeppelin: tutorial/zeppelin.md
+ - R: tutorial/viz-r.md
+ - Gallery: tutorial/viz-gallery.md
+ - Performance tuning:
+ - Benchmark: tutorial/benchmark.md
+ - Tune RDD application:
tutorial/Advanced-Tutorial-Tune-your-Application.md
+ - Sedona with Apache Flink:
+ - Spatial SQL app:
+ - Scala/Java: tutorial/flink/sql.md
- Examples:
- - Scala/Java: tutorial/demo.md
- - Python: tutorial/jupyter-notebook.md
- - Performance tuning:
- - Benchmark: tutorial/benchmark.md
- - Tune RDD application:
tutorial/Advanced-Tutorial-Tune-your-Application.md
+ - Scala/Java: tutorial/demo.md
+ - Python: tutorial/jupyter-notebook.md
- API Docs:
- - RDD (core):
- - Scala/Java doc: api/java-api.md
- - Python doc: api/python-api.md
- - R doc: api/r-api.md
- - SQL:
- - Quick start: api/sql/Overview.md
- - Vector data:
- - Constructor: api/sql/Constructor.md
- - Function: api/sql/Function.md
- - Predicate: api/sql/Predicate.md
- - Aggregate function: api/sql/AggregateFunction.md
- - Join query (optimizer): api/sql/Optimizer.md
- - Raster data:
- - Raster input and output: api/sql/Raster-loader.md
- - Raster operators: api/sql/Raster-operators.md
- - Parameter: api/sql/Parameter.md
- - Viz:
- - DataFrame/SQL: api/viz/sql.md
- - RDD: api/viz/java-api.md
+ - Sedona with Apache Spark:
+ - SQL:
+ - Quick start: api/sql/Overview.md
+ - Vector data:
+ - Constructor: api/sql/Constructor.md
+ - Function: api/sql/Function.md
+ - Predicate: api/sql/Predicate.md
+ - Aggregate function: api/sql/AggregateFunction.md
+ - Join query (optimizer): api/sql/Optimizer.md
+ - Raster data:
+ - Raster input and output: api/sql/Raster-loader.md
+ - Raster operators: api/sql/Raster-operators.md
+ - Parameter: api/sql/Parameter.md
+ - RDD (core):
+ - Scala/Java doc: api/java-api.md
+ - Python doc: api/python-api.md
+ - R doc: api/r-api.md
+ - Viz:
+ - DataFrame/SQL: api/viz/sql.md
+ - RDD: api/viz/java-api.md
+ - Sedona with Apache Flink:
+ - SQL:
+ - Overview: api/flink/Overview.md
+ - Constructor: api/flink/Constructor.md
+ - Function: api/flink/Function.md
+ - Predicate: api/flink/Predicate.md
- Community:
- Community: community/contact.md
- Contributing rule: community/rule.md
@@ -137,11 +156,11 @@ extra:
- icon: fontawesome/brands/twitter
link: 'https://twitter.com/ApacheSedona'
sedona:
- current_version: 1.1.1-incubating
- current_git_tag: sedona-1.1.1-incubating-rc1
- current_rc: 1.1.1-incubating-rc1
- current_snapshot: 1.2.0-incubating-SNAPSHOT
- next_version: 1.2.0-incubating
+ current_version: 1.2.0-incubating
+ current_git_tag: sedona-1.2.0-incubating-rc1
+ current_rc: 1.2.0-incubating-rc1
+ current_snapshot: 1.2.1-incubating-SNAPSHOT
+ next_version: 1.2.1-incubating
current_geotools: 1.1.0-25.2
copyright: Apache Sedona, Apache Incubator, Apache, the Apache feather logo,
and the Apache Incubator project logo are trademarks or registered trademarks
of The Apache Software Foundation. Copyright © 2021 The Apache Software
Foundation
markdown_extensions:
@@ -164,7 +183,8 @@ markdown_extensions:
- pymdownx.mark
- pymdownx.smartsymbols
- pymdownx.superfences
- - pymdownx.tabbed
+ - pymdownx.tabbed:
+ alternate_style: true
- pymdownx.tasklist:
custom_checkbox: true
- pymdownx.tilde
![https://www.dataiku.com/static/img/partners/LOGO-Blue-DME-PNG-3.png"](https://www.dataiku.com/static/img/partners/LOGO-Blue-DME-PNG-3.png"){kind=link}
![https://images.ukfast.co.uk/comms/news/businesscloud/photos/14-08-2018/gyana.jpg"](https://images.ukfast.co.uk/comms/news/businesscloud/photos/14-08-2018/gyana.jpg"){kind=link}
![https://149448277.v2.pressablecdn.com/wp-content/uploads/2021/03/guy-carpenter-logo-1.png"](https://149448277.v2.pressablecdn.com/wp-content/uploads/2021/03/guy-carpenter-logo-1.png"){kind=link}