Update docs related to new Jar name

benchmark/README.md

@@ -42,8 +42,8 @@ TPCH timing results is written to stdout in the following form: `TPCH_Result,<la
 
 ## CSharp
 1. Ensure that the Microsoft.Spark.Worker is properly [installed](../deployment/README.md#cloud-deployment) in your cluster.
-2. Build `microsoft-spark-<spark_majorversion.spark_minorversion.x>-<spark_dotnet_version>.jar` and the [CSharp Tpch benchmark](csharp/Tpch) application by following the [build instructions](../README.md#building-from-source).
-3. Upload [run_csharp_benchmark.sh](run_csharp_benchmark.sh), the Tpch benchmark application, and `microsoft-spark-<spark_majorversion.spark_minorversion.x>-<spark_dotnet_version>.jar` to the cluster.
+2. Build `microsoft-spark-<version>.jar` and the [CSharp Tpch benchmark](csharp/Tpch) application by following the [build instructions](../README.md#building-from-source).
+3. Upload [run_csharp_benchmark.sh](run_csharp_benchmark.sh), the Tpch benchmark application, and `microsoft-spark-<version>.jar` to the cluster.
 4. Run the benchmark by invoking:
     ```shell
     run_csharp_benchmark.sh \
@@ -53,7 +53,7 @@ TPCH timing results is written to stdout in the following form: `TPCH_Result,<la
     <executor_memory> \
     <executor_cores> \
     </path/to/Tpch.dll> \
-    </path/to/microsoft-spark-<spark_majorversion.spark_minorversion.x>-<spark_dotnet_version>.jar> \
+    </path/to/microsoft-spark-<version>.jar> \
     </path/to/Tpch executable> \
     </path/to/dataset> \
     <number of iterations> \

deployment/README.md

@@ -55,7 +55,7 @@ Microsoft.Spark.Worker is a backend component that lives on the individual worke
    foo@bar:~/path/to/app/bin/Release/netcoreapp2.1/ubuntu.16.04-x64/publish$ zip -r <your app>.zip .
    ```
 4. Upload the following to a distributed file system (e.g., HDFS, WASB, ADLS, S3, DBFS) that your cluster has access to:
-   * `microsoft-spark-<spark_majorversion.spark_minorversion.x>-<spark_dotnet_version>.jar` (Included as part of the [Microsoft.Spark](https://www.nuget.org/packages/Microsoft.Spark/) nuget and is colocated in your app's build output directory)
+   * `microsoft-spark-<version>.jar` (Included as part of the [Microsoft.Spark](https://www.nuget.org/packages/Microsoft.Spark/) nuget and is colocated in your app's build output directory)
    * `<your app>.zip`
    * Files (e.g., dependency files, common data accessible to every worker) or Assemblies (e.g., DLLs that contain your user-defined functions, libraries that your `app` depends on) to be placed in the working directory of each executor.
 
@@ -90,7 +90,7 @@ The following captures the setting for a HDInsight Script Action:
    --master yarn \
    --class org.apache.spark.deploy.dotnet.DotnetRunner \
    --files <comma-separated list of assemblies that contain UDF definitions, if any> \
-   adl://<cluster name>.azuredatalakestore.net/<some dir>/microsoft-spark-<spark_majorversion.spark_minorversion.x>-<spark_dotnet_version>.jar \
+   adl://<cluster name>.azuredatalakestore.net/<some dir>/microsoft-spark-<version>.jar \
    adl://<cluster name>.azuredatalakestore.net/<some dir>/<your app>.zip <your app> <app arg 1> <app arg 2> ... <app arg n>
    ```
 
@@ -104,7 +104,7 @@ foo@bar:~$ curl -k -v -X POST "https://<your spark cluster>.azurehdinsight.net/l
 -H "X-Requested-By: <hdinsight username>" \
 -d @- << EOF
 {
-    "file":"adl://<cluster name>.azuredatalakestore.net/<some dir>/microsoft-spark-<spark_majorversion.spark_minorversion.x>-<spark_dotnet_version>.jar",
+    "file":"adl://<cluster name>.azuredatalakestore.net/<some dir>/microsoft-spark-<version>.jar",
     "className":"org.apache.spark.deploy.dotnet.DotnetRunner",
     "files":["adl://<cluster name>.azuredatalakestore.net/<some dir>/<udf assembly>", "adl://<cluster name>.azuredatalakestore.net/<some dir>/<file>"],
     "args":["adl://<cluster name>.azuredatalakestore.net/<some dir>/<your app>.zip","<your app>","<app arg 1>","<app arg 2>,"...","<app arg n>"]
@@ -144,7 +144,7 @@ foo@bar:~$ aws emr create-cluster \
    --master yarn \
    --class org.apache.spark.deploy.dotnet.DotnetRunner \
    --files <comma-separated list of assemblies that contain UDF definitions, if any> \
-   s3://mybucket/<some dir>/microsoft-spark-<spark_majorversion.spark_minorversion.x>-<spark_dotnet_version>.jar \
+   s3://mybucket/<some dir>/microsoft-spark-<version>.jar \
    s3://mybucket/<some dir>/<your app>.zip <your app> <app args>
    ```
 
@@ -154,7 +154,7 @@ Amazon EMR Steps can be used to submit jobs to the Spark framework installed on
 # For example, you can run the following on Linux using `aws` cli.
 foo@bar:~$ aws emr add-steps \
 --cluster-id j-xxxxxxxxxxxxx \
---steps Type=spark,Name="Spark Program",Args=[--master,yarn,--files,s3://mybucket/<some dir>/<udf assembly>,--class,org.apache.spark.deploy.dotnet.DotnetRunner,s3://mybucket/<some dir>/microsoft-spark-<spark_majorversion.spark_minorversion.x>-<spark_dotnet_version>.jar,s3://mybucket/<some dir>/<your app>.zip,<your app>,<app arg 1>,<app arg 2>,...,<app arg n>],ActionOnFailure=CONTINUE
+--steps Type=spark,Name="Spark Program",Args=[--master,yarn,--files,s3://mybucket/<some dir>/<udf assembly>,--class,org.apache.spark.deploy.dotnet.DotnetRunner,s3://mybucket/<some dir>/microsoft-spark-<version>.jar,s3://mybucket/<some dir>/<your app>.zip,<your app>,<app arg 1>,<app arg 2>,...,<app arg n>],ActionOnFailure=CONTINUE
 ```
 
 ## Databricks
@@ -192,7 +192,7 @@ Databricks allows you to submit Spark .NET apps to an existing active cluster or
 
 One-time Setup:
    1. Go to your Databricks cluster -> Jobs (on the left-side menu) -> Set JAR
-   2. Upload the appropriate `microsoft-spark-<spark-version>-<spark-dotnet-version>.jar`
+   2. Upload the appropriate `microsoft-spark-<version>.jar`
    3. Set the params appropriately:
       ```
       Main Class: org.apache.spark.deploy.dotnet.DotnetRunner
@@ -231,5 +231,5 @@ Publishing your App & Running:
    1. [Create a Job](https://docs.databricks.com/user-guide/jobs.html) and select *Configure spark-submit*.
    2. Configure `spark-submit` with the following parameters:
       ```shell
-      ["--files","/dbfs/<path-to>/<app assembly/file to deploy to worker>","--class","org.apache.spark.deploy.dotnet.DotnetRunner","/dbfs/<path-to>/microsoft-spark-<spark_majorversion.spark_minorversion.x>-<spark_dotnet_version>.jar","/dbfs/<path-to>/<app name>.zip","<app name>","app arg1","app arg2"]
+      ["--files","/dbfs/<path-to>/<app assembly/file to deploy to worker>","--class","org.apache.spark.deploy.dotnet.DotnetRunner","/dbfs/<path-to>/microsoft-spark-<version>.jar","/dbfs/<path-to>/<app name>.zip","<app name>","app arg1","app arg2"]
       ```

docs/building/ubuntu-instructions.md

@@ -113,8 +113,9 @@ cd src/scala
 mvn clean package 
 ```
 You should see JARs created for the supported Spark versions:
-* `microsoft-spark-2.3.x/target/microsoft-spark-2.3.x-<version>.jar`
-* `microsoft-spark-2.4.x/target/microsoft-spark-2.4.x-<version>.jar`
+* `microsoft-spark-2-3/target/microsoft-spark-2-3_2.11-<version>.jar`
+* `microsoft-spark-2-4/target/microsoft-spark-2-4_2.11-<version>.jar`
+* `microsoft-spark-3-0/target/microsoft-spark-3-0_2.12-<version>.jar`
 
 ## Building .NET Sample Applications using .NET Core CLI
 

docs/building/windows-instructions.md

@@ -97,8 +97,9 @@ cd src\scala
 mvn clean package 
 ```
 You should see JARs created for the supported Spark versions:
-* `microsoft-spark-2.3.x\target\microsoft-spark-2.3.x-<version>.jar`
-* `microsoft-spark-2.4.x\target\microsoft-spark-2.4.x-<version>.jar`
+* `microsoft-spark-2-3\target\microsoft-spark-2-3_2.11-<version>.jar`
+* `microsoft-spark-2-4\target\microsoft-spark-2-4_2.11-<version>.jar`
+* `microsoft-spark-3-0\target\microsoft-spark-3-0_2.12-<version>.jar`
 
 ## Building .NET Samples Application
 

docs/deploy-worker-udf-binaries.md

@@ -110,6 +110,6 @@ spark-submit \
 --conf spark.yarn.appMasterEnv.DOTNET_WORKER_DIR=./worker/Microsoft.Spark.Worker-<version> \
 --conf spark.yarn.appMasterEnv.DOTNET_ASSEMBLY_SEARCH_PATHS=./udfs \
 --archives hdfs://<path to your files>/Microsoft.Spark.Worker.net461.win-x64-<version>.zip#worker,hdfs://<path to your files>/mySparkApp.zip#udfs \
-hdfs://<path to jar file>/microsoft-spark-2.4.x-<version>.jar \
+hdfs://<path to jar file>/microsoft-spark-<version>.jar \
 hdfs://<path to your files>/mySparkApp.zip mySparkApp
 ```

docs/getting-started/macos-instructions.md

@@ -68,7 +68,7 @@ These instructions will show you how to run a .NET for Apache Spark app using .N
     spark-submit \
     --class org.apache.spark.deploy.dotnet.DotnetRunner \
     --master local \
-    microsoft-spark-2.4.x-<version>.jar \
+    microsoft-spark-<version>.jar \
     dotnet HelloSpark.dll
     ```
     **Note**: This command assumes you have downloaded Apache Spark and added it to your PATH environment variable to be able to use `spark-submit`, otherwise, you would have to use the full path (e.g., `~/spark/bin/spark-submit`).

docs/getting-started/ubuntu-instructions.md

@@ -61,7 +61,7 @@ For detailed instructions, you can see [Building .NET for Apache Spark from Sour
     spark-submit \
     --class org.apache.spark.deploy.dotnet.DotnetRunner \
     --master local \
-    microsoft-spark-2.4.x-<version>.jar \
+    microsoft-spark-<version>.jar \
     dotnet HelloSpark.dll
     ```
     **Note**: This command assumes you have downloaded Apache Spark and added it to your PATH environment variable to be able to use `spark-submit`, otherwise, you would have to use the full path (e.g., `~/spark/bin/spark-submit`). For detailed instructions, you can see [Building .NET for Apache Spark from Source on Ubuntu](../building/ubuntu-instructions.md).

docs/getting-started/windows-instructions.md

@@ -49,7 +49,7 @@ For detailed instructions, you can see [Building .NET for Apache Spark from Sour
     spark-submit `
     --class org.apache.spark.deploy.dotnet.DotnetRunner `
     --master local `
-    microsoft-spark-2.4.x-<version>.jar `
+    microsoft-spark-<version>.jar `
     dotnet HelloSpark.dll
     ```
     **Note**: This command assumes you have downloaded Apache Spark and added it to your PATH environment variable to be able to use `spark-submit`, otherwise, you would have to use the full path (e.g., `c:\bin\apache-spark\bin\spark-submit`). For detailed instructions, you can see [Building .NET for Apache Spark from Source on Windows](../building/windows-instructions.md).