DOC-4573: Updates to remove partition ranges and parameters

modules/ROOT/nav.adoc

@@ -41,7 +41,6 @@
 * {cstar-data-migrator}
 ** xref:cdm-overview.adoc[]
 ** xref:cdm-steps.adoc[Migrate data]
-** xref:cdm-parameters.adoc[Parameters]
 
 * {dsbulk-loader}
 ** https://docs.datastax.com/en/dsbulk/overview/dsbulk-about.html[Overview]

modules/ROOT/pages/cassandra-data-migrator.adoc

@@ -1,4 +1,5 @@
 = {cstar-data-migrator}
+:page-aliases: cdm-parameters.adoc
 
 Use {cstar-data-migrator} to migrate and validate tables between origin and target Cassandra clusters, with available logging and reconciliation support.
 
@@ -42,55 +43,7 @@ include::partial$cdm-partition-ranges.adoc[]
 
 include::partial$cdm-guardrail-checks.adoc[]
 
+[[cdm-next-steps]]
+== Next steps
 
-[[cdm-reference]]
-== {cstar-data-migrator} references
-
-=== Common connection parameters for Origin and Target
-
-include::partial$common-connection-parameters.adoc[]
-
-=== Origin schema parameters
-
-include::partial$origin-schema-parameters.adoc[]
-
-=== Target schema parameters
-
-include::partial$target-schema-parameters.adoc[]
-
-=== Auto-correction parameters
-
-include::partial$auto-correction-parameters.adoc[]
-
-=== Performance and operations parameters
-
-include::partial$performance-and-operations-parameters.adoc[]
-
-=== Transformation parameters
-
-include::partial$transformation-parameters.adoc[]
-
-=== Cassandra filter parameters
-
-include::partial$cassandra-filter-parameters.adoc[]
-
-=== Java filter parameters
-
-include::partial$java-filter-parameters.adoc[]
-
-=== Constant column feature parameters
-
-include::partial$constant-column-feature-parameters.adoc[]
-
-=== Explode map feature parameters
-
-include::partial$explode-map-feature-parameters.adoc[]
-
-=== Guardrail feature parameter
-
-include::partial$guardrail-feature-parameters.adoc[]
-
-=== TLS (SSL) connection parameters
-
-include::partial$tls-ssl-connection-parameters.adoc[]
-
+For advanced operations, see documentation at https://github.com/datastax/cassandra-data-migrator[the repository].

modules/ROOT/partials/cdm-guardrail-checks.adoc

@@ -9,5 +9,5 @@ Example:
 --conf spark.cdm.schema.origin.keyspaceTable="<keyspacename>.<tablename>" \
 --conf spark.cdm.feature.guardrail.colSizeInKB=10000 \
 --master "local[*]" --driver-memory 25G --executor-memory 25G \
---class com.datastax.cdm.job.GuardrailCheck cassandra-data-migrator-4.x.x.jar &> logfile_name_$(date +%Y%m%d_%H_%M).txt
+--class com.datastax.cdm.job.GuardrailCheck cassandra-data-migrator-x.y.z.jar &> logfile_name_$(date +%Y%m%d_%H_%M).txt
 ----

modules/ROOT/partials/cdm-partition-ranges.adoc

@@ -1,35 +1,9 @@
-You can also use {cstar-data-migrator} to migrate or validate specific partition ranges. Use a **partition-file** with the name `./<keyspacename>.<tablename>_partitions.csv`.
-Use the following format in the CSV file, in the current folder as input. 
-Example:
-
-[source,csv]
-----
--507900353496146534,-107285462027022883
--506781526266485690,1506166634797362039
-2637884402540451982,4638499294009575633
-798869613692279889,8699484505161403540
-----
-
-Each line in the CSV represents a partition-range (`min,max`). 
-
-Alternatively, you can also pass the partition-file with a command-line parameter. 
-Example:
+You can also use {cstar-data-migrator} to xref:cdm-steps.adoc#cdm-steps[migrate] or xref:cdm-steps.adoc#cdm-validation-steps[validate] specific partition ranges by passing the below additional parameters.
 
 [source,bash]
 ----
-./spark-submit --properties-file cdm.properties \
- --conf spark.cdm.schema.origin.keyspaceTable="<keyspacename>.<tablename>" \
- --conf spark.cdm.tokenrange.partitionFile.input="/<path-to-file>/<csv-input-filename>" \
- --master "local[*]" --driver-memory 25G --executor-memory 25G \
- --class com.datastax.cdm.job.<Migrate|DiffData> cassandra-data-migrator-x.y.z.jar &> logfile_name_$(date +%Y%m%d_%H_%M).txt
+--conf spark.cdm.filter.cassandra.partition.min=<token-range-min>
+--conf spark.cdm.filter.cassandra.partition.max=<token-range-max>
 ----
 
-This mode is specifically useful to process a subset of partition-ranges that may have failed during a previous run.
-
-[NOTE]
-====
-In the format shown above, the migration and validation jobs autogenerate a file named `./<keyspacename>.<tablename>_partitions.csv`.
-The file contains any failed partition ranges.
-No file is created if there were no failed partitions.
-You can use the CSV as input to process any failed partition in a subsequent run.
-====
+This mode is specifically useful to process a subset of partition-ranges.

modules/ROOT/partials/cdm-prerequisites.adoc

@@ -2,15 +2,15 @@ Read the prerequisites below before using the Cassandra Data Migrator.
 
 * Install or switch to Java 11.
 The Spark binaries are compiled with this version of Java.
-* Select a single VM to run this job and install https://archive.apache.org/dist/spark/spark-3.5.1/[Spark 3.5.1] there.
-No cluster is necessary.
-* Optionally, install https://maven.apache.org/download.cgi[Maven] 3.9.x if you want to build the JAR for local development.
+* Select a single VM to run this job and install https://archive.apache.org/dist/spark/spark-3.5.3/[Spark 3.5.3] there.
+No cluster is necessary for most one-time migrations. However, Spark cluster mode is also supported for complex migrations.
+* Optionally, install https://maven.apache.org/download.cgi[Maven] `3.9.x` if you want to build the JAR for local development.
 
 Run the following commands to install Apache Spark:
 
 [source,bash]
 ----
-wget https://archive.apache.org/dist/spark/spark-3.5.1/spark-3.5.1-bin-hadoop3-scala2.13.tgz
+wget https://archive.apache.org/dist/spark/spark-3.5.3/spark-3.5.3-bin-hadoop3-scala2.13.tgz
 
-tar -xvzf spark-3.5.1-bin-hadoop3-scala2.13.tgz
+tar -xvzf spark-3.5.3-bin-hadoop3-scala2.13.tgz
 ----

modules/ROOT/partials/cdm-validation-steps.adoc

@@ -41,6 +41,6 @@ spark.cdm.autocorrect.mismatch                    false|true
 
 [IMPORTANT]
 ====
-The {cstar-data-migrator} validation job never deletes records from the target cluster.
+The {cstar-data-migrator} validation job never deletes records from the source or target clusters.
 The job only adds or updates data on the target cluster.
 ====