Updated NOTICE file for 2.6.0

Also bumped reference to version in docs. Will bump actual version on release branch.

Author: rjrudin

NOTICE.txt

@@ -13,17 +13,20 @@ Third Party Notices
 jackson-dataformat-xml 2.15.2 (Apache-2.0)
 jdom2 2.0.6.1 (Apache-2.0)
 jena-arq 4.10.0 (Apache-2.0)
-langchain4j 0.35.0 (Apache-2.0)
+langchain4j 1.0.0-beta2 (Apache-2.0)
 marklogic-client-api 7.1.0 (Apache-2.0)
 okhttp 4.12.0 (Apache-2.0)
+Semaphore-CS-Client 5.6.1 (Apache-2.0)
+Semaphore-Cloud-Client 5.6.1 (Apache-2.0)
+tika-core 3.1.0 (Apache-2.0)
 
 Common Licenses
 
 Apache License 2.0 (Apache-2.0)
 
 Third-Party Components
 
-The following is a list of the third-party components used by the MarkLogic® Spark connector 2.5.1 (last updated January 7, 2025):
+The following is a list of the third-party components used by the MarkLogic® Spark connector 2.6.0 (last updated May 1, 2025):
 
 jackson-dataformat-xml 2.15.2 (Apache-2.0)
 https://repo1.maven.org/maven2/com/fasterxml/jackson/dataformat/jackson-dataformat-xml/
@@ -37,7 +40,7 @@ jena-arq 4.10.0 (Apache-2.0)
 https://repo1.maven.org/maven2/org/apache/jena/jena-arq/
 For the full text of the Apache-2.0 license, see Apache License 2.0 (Apache-2.0)
 
-langchain4j 0.35.0 (Apache-2.0)
+langchain4j 1.0.0-beta2 (Apache-2.0)
 https://repo1.maven.org/maven2/dev/langchain4j/langchain4j/
 For the full text of the Apache-2.0 license, see Apache License 2.0 (Apache-2.0)
 
@@ -49,10 +52,21 @@ okhttp 4.12.0 (Apache-2.0)
 https://repo1.maven.org/maven2/com/squareup/okhttp3/okhttp/
 For the full text of the Apache-2.0 license, see Apache License 2.0 (Apache-2.0)
 
+Semaphore-CS-Client 5.6.1 (Apache-2.0)
+https://repo1.maven.org/maven2/com/smartlogic/csclient/Semaphore-CS-Client/
+For the full text of the Apache-2.0 license, see Apache License 2.0 (Apache-2.0)
+
+Semaphore-CS-Client 5.6.1 (Apache-2.0)
+https://repo1.maven.org/maven2/com/smartlogic/cloud/Semaphore-Cloud-Client/
+For the full text of the Apache-2.0 license, see Apache License 2.0 (Apache-2.0)
+
+tika-core 3.1.0 (Apache-2.0)
+https://repo1.maven.org/maven2/org/apache/tika/tika-core/
+For the full text of the Apache-2.0 license, see Apache License 2.0 (Apache-2.0)
 
 Common Licenses
 
-The following is a list of the third-party components used by the MarkLogic® Spark connector 2.5.1 (last updated January 7, 2025):
+The following is a list of the third-party components used by the MarkLogic® Spark connector 2.6.0 (last updated May 1, 2025):
 
 Apache License 2.0 (Apache-2.0)
 https://spdx.org/licenses/Apache-2.0.html

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-2.5.1.jar" pyspark-shell'
+os.environ['PYSPARK_SUBMIT_ARGS'] = '--jars "/path/to/marklogic-spark-connector-2.6.0.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-2.5.1.jar` should be changed to match the location of the connector 
+The path of `/path/to/marklogic-spark-connector-2.6.0.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

@@ -30,7 +30,7 @@ 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-2.5.1.jar
+    pyspark --jars marklogic-spark-connector-2.6.0.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/getting-started/setup.md

@@ -31,10 +31,10 @@ have an instance of MarkLogic running, you can skip step 4 below, but ensure tha
 extracted directory contains valid connection properties for your instance of MarkLogic.
 
 1. From [this repository's Releases page](https://github.com/marklogic/marklogic-spark-connector/releases), select 
-   the latest release and download the `marklogic-spark-getting-started-2.5.1.zip` file.
+   the latest release and download the `marklogic-spark-getting-started-2.6.0.zip` file.
 2. Extract the contents of the downloaded zip file. 
 3. Open a terminal window and go to the directory created by extracting the zip file; the directory should have a 
-   name of "marklogic-spark-getting-started-2.5.1".
+   name of "marklogic-spark-getting-started-2.6.0".
 4. Run `docker-compose up -d` to start an instance of MarkLogic
 5. Ensure that the `./gradlew` file is executable; depending on your operating system, you may need to run
    `chmod 755 gradlew` to make the file executable.

examples/entity-aggregation/build.gradle

@@ -8,7 +8,7 @@ repositories {
 
 dependencies {
   implementation 'org.apache.spark:spark-sql_2.12:3.5.5'
-  implementation "com.marklogic:marklogic-spark-connector:2.5.1"
+  implementation "com.marklogic:marklogic-spark-connector:2.6.0"
   implementation "org.postgresql:postgresql:42.7.4"
 }
 

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

@@ -9,7 +9,7 @@
    "source": [
     "# Make the MarkLogic connector available to the underlying PySpark application.\n",
     "import os\n",
-    "os.environ['PYSPARK_SUBMIT_ARGS'] = '--jars \"marklogic-spark-connector-2.5.1.jar\" pyspark-shell'\n",
+    "os.environ['PYSPARK_SUBMIT_ARGS'] = '--jars \"marklogic-spark-connector-2.6.0.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",
@@ -64,9 +64,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Group employees by State and then calculate the max base salary across each department, sorting on \n",
-    "# the max base salary in the Engineering department. Then plot the data by converting the Spark DataFrame to \n",
-    "# a pandas DataFrame - https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.html . \n",
+    "# Group employees by State and then calculate the max base salary across each department, sorting on\n",
+    "# the max base salary in the Engineering department. Then plot the data by converting the Spark DataFrame to\n",
+    "# a pandas DataFrame - https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.html .\n",
     "\n",
     "from pyspark.sql.functions import desc\n",
     "df.groupBy(\"State\") \\\n",

examples/java-dependency/build.gradle

@@ -8,7 +8,7 @@ repositories {
 
 dependencies {
   implementation 'org.apache.spark:spark-sql_2.12:3.5.5'
-  implementation 'com.marklogic:marklogic-spark-connector:2.5.1'
+  implementation 'com.marklogic:marklogic-spark-connector:2.6.0'
 }
 
 task runApp(type: JavaExec) {