[DOCS] azure synapse analytics (#1673)

* docs: add tutorial for installing Sedona on Azure Synapse Analytics with DEP enabled

* link to main docs index, rename file

* fix linting
fix tone
fix context build
add a preface note about why we're using specific version and not latest
remove author info
explain more about numpy issue

* add org.apache.sedona.sql.SedonaSqlExtensions

* is in fact required:         .config('spark.jars.packages',
                'org.apache.sedona:sedona-spark-shaded-3.4_2.12-1.6.1,'
                'org.datasyslab:geotools-wrapper-1.6.1-28.2') \

* fix 4 blank lines, 2 trailing spaces

* fix typos. fix tone

* fix end of files

* undo bad markdown and pass pre-commit

* grammar

---------

Co-authored-by: Tim Downs <[email protected]>

docs/setup/azure-synapse-analytics.md

@@ -0,0 +1,220 @@
+This tutorial will guide you through the process of installing Sedona on Azure Synapse Analytics when Data Exfiltration Protection (DEP) is enabled or when you have no internet connection from the Spark pools due to other networking constraints.
+
+## Before you begin
+
+This tutorial focuses on getting you up and running with Sedona 1.6.1 on Spark 3.4 Python 3.10
+
+If you want to run newer version, you will need to dive into the detailed build and diagnose process detailed in the lower part of this document.
+
+## Strong recommendations
+
+1. Start with a clean Spark pool with no other packages installed to avoid package conflicts.
+2. Apache Spark pool -> Apache Spark configuration: Use default configuration
+
+## Sedona 1.6.1 on Spark 3.4 Python 3.10
+
+### Step1: Download packages (9)
+
+Caution: Precise versions are critical, latest is not always greatest here.
+
+From Maven
+
+- [sedona-spark-shaded-3.4_2.12-1.6.1.jar](https://mvnrepository.com/artifact/org.apache.sedona/sedona-spark-shaded-3.4_2.12/1.6.1)
+
+- [geotools-wrapper-1.6.1-28.2.jar](https://mvnrepository.com/artifact/org.datasyslab/geotools-wrapper/1.6.1-28.2)
+
+From PyPi
+
+- [rasterio-1.4.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl](https://files.pythonhosted.org/packages/cd/ad/2d3a14e5a97ca827a38d4963b86071267a6cd09d45065cd753d7325699b6/rasterio-1.4.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl)
+
+- [shapely-2.0.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl](https://files.pythonhosted.org/packages/2b/a6/302e0d9c210ccf4d1ffadf7ab941797d3255dcd5f93daa73aaf116a4db39/shapely-2.0.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl)
+
+- [apache_sedona-1.6.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl](https://files.pythonhosted.org/packages/b6/71/09f7ca2b6697b2699c04d1649bb379182076d263a9849de81295d253220d/apache_sedona-1.6.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl)
+
+- [click_plugins-1.1.1-py2.py3-none-any.whl](https://files.pythonhosted.org/packages/e9/da/824b92d9942f4e472702488857914bdd50f73021efea15b4cad9aca8ecef/click_plugins-1.1.1-py2.py3-none-any.whl)
+
+- [cligj-0.7.2-py3-none-any.whl](https://files.pythonhosted.org/packages/73/86/43fa9f15c5b9fb6e82620428827cd3c284aa933431405d1bcf5231ae3d3e/cligj-0.7.2-py3-none-any.whl)
+
+- [affine-2.4.0-py3-none-any.whl](https://files.pythonhosted.org/packages/0b/f7/85273299ab57117850cc0a936c64151171fac4da49bc6fba0dad984a7c5f/affine-2.4.0-py3-none-any.whl)
+
+- [numpy-2.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl](https://files.pythonhosted.org/packages/fb/25/ba023652a39a2c127200e85aed975fc6119b421e2c348e5d0171e2046edb/numpy-2.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl)
+
+### Step 2: Upload packages to Synapse Workspace
+
+https://learn.microsoft.com/en-us/azure/synapse-analytics/spark/apache-spark-manage-workspace-packages
+
+### Step 3: Add packages to Spark Pool
+
+This tutorial used the second method on this page: **If you are updating from the Synapse Studio**
+
+https://learn.microsoft.com/en-us/azure/synapse-analytics/spark/apache-spark-manage-pool-packages#manage-packages-from-synapse-studio-or-azure-portal
+
+### Step 4: Notebook
+
+Start your notebook with:
+
+```python
+from sedona.spark import SedonaContext
+
+config = SedonaContext.builder() \
+    .config('spark.jars.packages',
+            'org.apache.sedona:sedona-spark-shaded-3.4_2.12-1.6.1,'
+            'org.datasyslab:geotools-wrapper-1.6.1-28.2') \
+    .config("spark.serializer","org.apache.spark.serializer.KryoSerializer") \
+    .config("spark.kryo.registrator", "org.apache.sedona.core.serde.SedonaKryoRegistrator") \
+    .config("spark.sql.extensions", "org.apache.sedona.viz.sql.SedonaVizExtensions,org.apache.sedona.sql.SedonaSqlExtensions") \
+    .getOrCreate()
+
+sedona = SedonaContext.create(config)
+```
+
+Run a test
+
+```python
+sedona.sql("SELECT ST_GeomFromEWKT('SRID=4269;POINT(40.7128 -74.0060)')").show()
+```
+
+If you see the output of the point, then the installation is successful. Are you are all done with the setup.
+
+## Packages for Sedona 1.6.0 on Spark 3.4 Python 10
+
+```
+spark-xml_2.12-0.17.0.jar
+sedona-spark-shaded-3.4_2.12-1.6.0.jar
+
+click_plugins-1.1.1-py2.py3-none-any.whl
+affine-2.4.0-py3-none-any.whl
+apache_sedona-1.6.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
+cligj-0.7.2-py3-none-any.whl
+rasterio-1.3.10-cp310-cp310-manylinux2014_x86_64.whl
+shapely-2.0.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
+snuggs-1.4.7-py3-none-any.whl
+geotools-wrapper-1.6.0-28.2.jar
+```
+
+## Background: How to identify packages for other/future versions of Spark and/or Sedona
+
+Warning: this process is going to require some tenacious technical skills and troubleshooting.
+
+Broad steps: build a linux VM from the same image as the deployed Spark Pool, configure for Synapse, install Sedona packages, identify required packages over and above baseline Synapse config.
+
+This is the process for Sedona 1.6.1 on Spark 3.4 Python 3.10. (The same process was used for Sedona 1.6.0)
+
+### Step 1: Identify the Linux image of the Spark Pool by version
+
+https://learn.microsoft.com/en-us/azure/synapse-analytics/spark/apache-spark-34-runtime
+
+### Step 2 : Download the ISO
+
+https://github.com/microsoft/azurelinux/tree/2.0
+
+### Step 3: build the VM
+
+https://github.com/microsoft/azurelinux/blob/2.0/toolkit/docs/quick_start/quickstart.md#iso-image
+
+Important settings if using Hyper-V
+
+- Enable Secure Boot: Microsoft UEFI Certificate authority
+- Cores 2
+- Disable Dynamic Memory (fix at 8Gb), forgetting this setting causes havoc.
+
+### Step 4: patch the VM
+
+Connect the VM. Note: it will take longer to first boot than you'd expect
+
+```sh
+sudo dnf upgrade
+```
+
+### Step 5: optional but strongly recommended - install ssh-server (for best copy and paste experience)
+
+```sh
+sudo tdnf install -y openssh-server
+```
+
+Enable root and password auth
+
+```sh
+sudo vi /etc/ssh/sshd_config
+-	PasswordAuthentication yes
+-	PermitRootLogin yes
+```
+
+Start ssh-server
+
+```bash
+sudo systemctl enable --now sshd.service
+```
+
+Identify the ip of the VM (I'm using Hyper-V on windows 10 desktop)
+
+```ps
+Get-VMNetworkAdapter -VMName "Synapse Spark 3.4 Python 3.10 Sedona 1.6.1" | Select-Object -ExpandProperty IPAddresses
+```
+
+### Step 6: install Miniconda
+
+```bash
+cd /tmp
+wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
+chmod +x Miniconda3-latest-Linux-x86_64.sh
+./Miniconda3-latest-Linux-x86_64.sh
+```
+
+### Step 7: install compilers
+
+```sh
+sudo tdnf -y install gcc g++
+```
+
+### Step 8: create baseline synapse virtual env
+
+Download the virtual env spec
+
+```bash
+wget -O Synapse-Python310-CPU.yml https://raw.githubusercontent.com/microsoft/synapse-spark-runtime/refs/heads/main/Synapse/spark3.4/Synapse-Python310-CPU.yml source
+```
+
+```bash
+conda env create -f Synapse-Python310-CPU.yml -n synapse
+```
+
+if you get errors due to `fsspec_wrapper` then remove `fsspec_wrapper==0.1.13=py_3` from the yml and run again
+
+if you get further but different errors from `pip` after making the above change, ignore them you can still proceed
+
+### Step 9: install sedona python packages
+
+```bash
+conda activate synapse
+echo "apache-sedona==1.6.1" > requirements.txt
+pip install -r requirements.txt > pip-output.txt
+```
+
+### Step 10: identify Python packages to download
+
+```bash
+grep Downloading pip-output.txt
+```
+
+**This will be the list of packages you need to locate and download from PyPi**
+
+Example output
+
+```
+Downloading apache_sedona-1.6.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (177 kB)
+Downloading shapely-2.0.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.5 MB)
+Downloading rasterio-1.4.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (22.2 MB)
+Downloading affine-2.4.0-py3-none-any.whl (15 kB)
+Downloading cligj-0.7.2-py3-none-any.whl (7.1 kB)
+Downloading click_plugins-1.1.1-py2.py3-none-any.whl (7.5 kB)
+```
+
+### Step 11: identify package conflicts in your deployed Azure Synapse Spark Pool (the real one, not the VM)
+
+- upload packages to workspace
+- add packages to your (clean!) Spark pool
+
+Pay careful attention to errors reported back from Synpase and troubleshoot to resolve conflicts.
+
+Note: We didn't have issues with Sedona 1.6.0 on Spark 3.4, but Sedona 1.6.1 and supporting packages had a conflict around `numpy` which requires us to download a specific version and add it to the packages list. `numpy` was not listed in the output of the grep.

mkdocs.yml

@@ -26,6 +26,7 @@ nav:
           - Install on AWS Glue: setup/glue.md
           - Install on Microsoft Fabric: setup/fabric.md
           - Set up Spark cluster manually: setup/cluster.md
+          - Install on Azure Synpase Analytics: setup/azure-synapse-analytics.md
       - Install with Apache Flink:
           - Install Sedona Scala/Java: setup/flink/install-scala.md
       - Install with Snowflake: