Updating docs for 2.1.0

Included bit about needing eval/invoke privileges for the new custom code feature.

Author: rjrudin

docs/getting-started/jupyter.md

@@ -32,15 +32,15 @@ connector and also to initialize Spark:
 
 ```
 import os
-os.environ['PYSPARK_SUBMIT_ARGS'] = '--jars "/path/to/marklogic-spark-connector-2.0.0.jar" pyspark-shell'
+os.environ['PYSPARK_SUBMIT_ARGS'] = '--jars "/path/to/marklogic-spark-connector-2.1.0.jar" pyspark-shell'
 
 from pyspark.sql import SparkSession
 spark = SparkSession.builder.master("local[*]").appName('My Notebook').getOrCreate()
 spark.sparkContext.setLogLevel("WARN")
 spark
 ```
 
-The path of `/path/to/marklogic-spark-connector-2.0.0.jar` should be changed to match the location of the connector 
+The path of `/path/to/marklogic-spark-connector-2.1.0.jar` should be changed to match the location of the connector 
 jar on your filesystem. You are free to customize the `spark` variable in any manner you see fit as well. 
 
 Now that you have an initialized Spark session, you can run any of the examples found in the 

docs/getting-started/pyspark.md

@@ -29,7 +29,7 @@ shell by pressing `ctrl-D`.
 
 Run PySpark from the directory that you downloaded the connector to per the [setup instructions](setup.md):
 
-    pyspark --jars marklogic-spark-connector-2.0.0.jar
+    pyspark --jars marklogic-spark-connector-2.1.0.jar
 
 The `--jars` command line option is PySpark's method for utilizing Spark connectors. Each Spark environment should have
 a similar mechanism for including third party connectors; please see the documentation for your particular Spark

docs/reading.md

@@ -284,6 +284,10 @@ useful when you need to retrieve data that cannot be easily accessed via Optic,
 to that of [MarkLogic's CoRB tool](https://github.com/marklogic-community/corb2) for processing data already in 
 MarkLogic. 
 
+When using this feature, please ensure that your MarkLogic user has the required privileges for the 
+MarkLogic REST [eval endpoint](https://docs.marklogic.com/REST/POST/v1/eval) and 
+[invoke endpoint](https://docs.marklogic.com/REST/POST/v1/invoke).
+
 Custom code can be [written in JavaScript](https://docs.marklogic.com/guide/getting-started/javascript) by 
 configuring the `spark.marklogic.read.javascript` option:
 

docs/writing.md

@@ -189,6 +189,10 @@ To easily support that use case, the connector defaults to assuming that each ro
 column named "URI" of type string. This matches the convention for reading rows via custom code, which defaults to the
 same schema. User-defined custom code is then expected to declare an external variable named "URI".
 
+When using this feature, please ensure that your MarkLogic user has the required privileges for the
+MarkLogic REST [eval endpoint](https://docs.marklogic.com/REST/POST/v1/eval) and
+[invoke endpoint](https://docs.marklogic.com/REST/POST/v1/invoke).
+
 The following shows an example of reading and processing rows via custom code specified by 
 `spark.marklogic.write.javascript`, where each row is expected to have a single column named "URI" (the script for
 reading rows only returns the first 10 URIs to make it easier to verify that the correct data is logged; you can

examples/entity-aggregation/build.gradle

@@ -7,8 +7,8 @@ repositories {
 }
 
 dependencies {
-  implementation 'org.apache.spark:spark-sql_2.12:3.3.2'
-  implementation "com.marklogic:marklogic-spark-connector:2.0.0"
+  implementation 'org.apache.spark:spark-sql_2.12:3.4.1'
+  implementation "com.marklogic:marklogic-spark-connector:2.1.0"
   implementation "org.postgresql:postgresql:42.6.0"
 }
 

examples/getting-started/build.gradle

@@ -1,6 +1,6 @@
 plugins {
   id 'net.saliman.properties' version '1.5.2'
-  id "com.marklogic.ml-gradle" version "4.5.1"
+  id "com.marklogic.ml-gradle" version "4.6.0"
 }
 
 repositories {

examples/getting-started/gradle/wrapper/gradle-wrapper.properties

@@ -1,5 +1,5 @@
 distributionBase=GRADLE_USER_HOME
 distributionPath=wrapper/dists
-distributionUrl=https\://services.gradle.org/distributions/gradle-7.5.1-bin.zip
+distributionUrl=https\://services.gradle.org/distributions/gradle-8.4-bin.zip
 zipStoreBase=GRADLE_USER_HOME
 zipStorePath=wrapper/dists

examples/getting-started/marklogic-spark-getting-started.ipynb

@@ -53,7 +53,7 @@
    "source": [
     "# Make the MarkLogic connector available to the underlying PySpark application.\n",
     "import os\n",
-    "os.environ['PYSPARK_SUBMIT_ARGS'] = '--jars \"marklogic-spark-connector-2.0.0.jar\" pyspark-shell'\n",
+    "os.environ['PYSPARK_SUBMIT_ARGS'] = '--jars \"marklogic-spark-connector-2.1.0.jar\" pyspark-shell'\n",
     "\n",
     "# Define the connection details for the getting-started example application.\n",
     "client_uri = \"spark-example-user:password@localhost:8003\"\n",

examples/java-dependency/build.gradle

@@ -3,13 +3,12 @@ plugins {
 }
 
 repositories {
-  mavenLocal()
   mavenCentral()
 }
 
 dependencies {
   implementation 'org.apache.spark:spark-sql_2.12:3.4.1'
-  implementation 'com.marklogic:marklogic-spark-connector:2.1-SNAPSHOT'
+  implementation 'com.marklogic:marklogic-spark-connector:2.1.0'
 }
 
 task runApp(type: JavaExec) {