Analytics updates - post-GA EA

modules/ROOT/examples/Columnar.py

@@ -2,14 +2,14 @@
 
 # tag::init[]
 spark = (SparkSession.builder
-    .appName("Couchbase Spark Connector Columnar Example")
+    .appName("Couchbase Spark Connector Capella Analytics Example")
     # Note whether you need the .master(...) and .config("spark.jars"...) lines depends on how you are using Spark.
     # See our PySpark documentation for more details.
     .master("local[*]")
     .config("spark.jars", "/path/to/spark-connector-assembly-<version>.jar")
-    .config("spark.couchbase.connectionString", "couchbases://cb.your.columnar.connection.string.com")
-    .config("spark.couchbase.username", "YourColumnarUsername")
-    .config("spark.couchbase.password", "YourColumnarPassword")
+    .config("spark.couchbase.connectionString", "couchbases://cb.your.capella.analytics.connection.string.com")
+    .config("spark.couchbase.username", "YourCapellaUsername")
+    .config("spark.couchbase.password", "YourCapellaPassword")
     .getOrCreate())
 # end::init[]
 

modules/ROOT/examples/Columnar.scala

@@ -4,9 +4,9 @@ object Columnar {
   // tag::init[]
   val spark = SparkSession
     .builder()
-    .appName("Couchbase Spark Connector Columnar Example") // your app name
+    .appName("Couchbase Spark Connector Capella Analytics Example") // your app name
     .master("local[*]") // your local or remote Spark master node
-    .config("spark.couchbase.connectionString", "couchbases://your-columnar-endpoint.cloud.couchbase.com")
+    .config("spark.couchbase.connectionString", "couchbases://your-capella-analytics-endpoint.cloud.couchbase.com")
     .config("spark.couchbase.username", "username")
     .config("spark.couchbase.password", "password")
     .getOrCreate()

modules/ROOT/nav.adoc

@@ -8,7 +8,7 @@
 * xref:java-api.adoc[Java API]
 * xref:streaming.adoc[Structured Streaming Support]
 * xref:spark-shell.adoc[Using the Spark Shell]
-* xref:columnar.adoc[Columnar Support]
+* xref:enterprise-analytics.adoc[Analytics Support]
 * xref:databricks.adoc[Databricks Support]
 * xref:configuration.adoc[Configuration]
 * xref:release-notes.adoc[Release Notes]

modules/ROOT/pages/columnar.adoc → modules/ROOT/pages/enterprise-analytics.adoc

@@ -1,17 +1,20 @@
-= Capella Columnar Support
-:nav-title: Columnar Support
+= Enterprise Analytics Support
+:nav-title: Analytics Support
+:page-aliases: columnar.adoc
+:description: Connecting to Capella Analytics or Enterprise Analytics cluster is very similar to connecting to any Couchbase cluster. 
 
 
 [abstract]
-Connecting to Capella Columnar is very similar to connecting to any Couchbase cluster. This section explains how.
+{description}
+This section explains how.
 
-Capella Columnar clusters can be connected to using either Scala or PySpark.
+Capella Analytics or Enterprise Analytics clusters can be connected to using either Scala or PySpark.
 To get bootstrapped, users should view the xref:getting-started.adoc[Scala getting started] or xref:pyspark.adoc[PySpark getting started] guides.
 
 
 == Spark Configuration
 
-The first step as usual is to create a `SparkSession`, here connecting to your Capella Columnar cluster.
+The first step as usual is to create a `SparkSession`, here connecting to your Capella Analytics or Enterprise Analytics cluster.
 This works just like connecting to any other type of Couchbase cluster.
 
 [{tabs}]
@@ -136,5 +139,5 @@ include::example$Columnar.py[tag=sql,indent=0]
 --
 ====
 
-Note this SQL is executed purely within Spark, and is not sent to the Capella Columnar cluster.
+Note this SQL is executed purely within Spark, and is not sent to the Analytics cluster.
 

modules/ROOT/pages/index.adoc

@@ -11,7 +11,7 @@ Please see one of the following getting started guide:
 * xref:pyspark.adoc[PySpark getting started].
 * xref:java-api.adoc[Java getting started].
 
-The Couchbase Spark Connector supports any type of Couchbase cluster.  Users of Capella Columnar should see the xref:columnar.adoc[Columnar Support] page.
+The Couchbase Spark Connector supports any type of Couchbase cluster.  Users of Capella Analytics or Enterprise Analytics should see the xref:enterprise-analytics.adoc[Analytics Support] page.
 
 == Compatibility
 

modules/ROOT/pages/spark-sql.adoc

@@ -1,6 +1,6 @@
 = DataFrames, Datasets, and SQL
 :page-topic-type: concept
-:description: Spark allows accessing query, analytics, Enterprise Analytics, and Capella Columnar in powerful and convenient ways.
+:description: Spark allows accessing query, analytics, Enterprise Analytics, and Capella Analytics, in powerful and convenient ways.
 
 
 [abstract]
@@ -12,7 +12,9 @@ Let's see how to use those with Couchbase.
 Before you can create DataFrames or Datasets with Couchbase, you need to create a `SparkSession`.
 See xref:getting-started.adoc[Getting Started (Scala)] or xref:pyspark.adoc[Getting Start(PySpark)]
 
+
 == Running examples
+
 All query examples presented on this page at least require the `travel-sample` dataset to be installed on your Couchbase cluster, with a primary index.
 If you haven't done so already, you can create a primary index by executing this {sqlpp} statement: `pass:c[CREATE PRIMARY INDEX ON `travel-sample`]`.
 
@@ -23,7 +25,22 @@ Enterprise Analytics is also supported, and provides enhanced analytics capabili
 == DataFrames
 
 A read `DataFrame` can be created through `spark.read.format(...)`, and which format to choose depends on the type of service you want to use.
-For `spark.read`, `couchbase.query`, `couchbase.analytics`, `couchbase.enterprise-analytics`, and `couchbase.columnar` are available.
+For `spark.read` -- `couchbase.query`, `couchbase.analytics`, `couchbase.enterprise-analytics`, and `couchbase.columnar` are available.
+
+
+.Spark DataFrame Creation by Analytics Service
+|===
+| Analytics solution | Spark method
+
+a| xref:enterprise-analytics:intro:intro.adoc[Enterprise Analytics]
+| `couchbase.enterprise-analytics`
+
+a| xref:analytics:intro:intro.adoc[Capella Analytics] -- _formerly known as Columnar_
+| `couchbase.columnar`
+
+a| xref:server:learn:services-and-indexes/services/analytics-service.adoc[CBAS (Couchbase Analytics Service)] -- row-based analytics in operational clusters (self-managed or Capella Operational)
+| `couchbase.analytics`
+|===
 
 (For reading from the KV service - see xref:working-with-rdds.adoc[RDDs])
 
@@ -60,7 +77,7 @@ PySpark::
 ----
 include::example$DataFrames.py[tag=query-collection,indent=0]
 ----
-Scala (Columnar)::
+Scala (Capella Analytics, _a.k.a._ Columnar)::
 +
 --
 [source,scala]
@@ -86,7 +103,9 @@ include::example$DataFrames.py[tag=enterprise-analytics-collection,indent=0]
 --
 ====
 
-Note all query options are documented here xref:_query_options[Query Options], all Capella Columnar options here xref:_columnar_options[Capella Columnar options], and all Enterprise Analytics options here xref:_enterprise_analytics_options[Enterprise Analytics options].
+Note, all query options are documented in xref:_query_options[Query Options], 
+all Capella Analytics options in xref:_columnar_options[Capella Analytics options], 
+and all Enterprise Analytics options in xref:_enterprise_analytics_options[Enterprise Analytics options].
 
 If you will usually be using the same collection, it can be more convenient to provide it in the SparkSession config instead:
 
@@ -111,13 +130,13 @@ We can limit both the inference and the {sqlpp} executed from the DataFrame to o
 
 [{tabs}]
 ====
-Scala (Columnar)::
+Scala (Capella Analytics, _a.k.a._ Columnar)::
 +
 [source,scala]
 ----
 include::example$SparkSQL.scala[tag=queryfilter,indent=0]
 ----
-PySpark (Columnar)::
+PySpark (Capella Analytics, _a.k.a._ Columnar)::
 +
 [source,python]
 ----
@@ -595,6 +614,7 @@ The available options for Enterprise Analytics DataFrame and Dataset operations:
 
 [#_kv_options]
 === KeyValue options
+
 The available options for query DataFrame and Dataset operations:
 
 .KeyValue Options
@@ -670,7 +690,8 @@ The available options for query DataFrame and Dataset operations:
 
 
 [#_columnar_options]
-=== Capella Columnar options
+=== Capella Analytics options
+
 The available options for Capella Columnar DataFrame and Dataset operations:
 
 .Capella Columnar Options
@@ -680,17 +701,17 @@ The available options for Capella Columnar DataFrame and Dataset operations:
 
 | "database"
 | ColumnarOptions.Database
-| Name of a Couchbase Columnar database
+| Name of a Couchbase Analytics database
 | Mandatory
 
 | "scope"
 | ColumnarOptions.Scope
-| Name of a Couchbase Columnar scope
+| Name of a Couchbase Analytics scope
 | Mandatory
 
 | "collection"
 | ColumnarOptions.Collection
-| Name of a Couchbase Columnar collection
+| Name of a Couchbase Analytics collection
 | Mandatory
 
 | "timeout"
@@ -705,7 +726,7 @@ The available options for Capella Columnar DataFrame and Dataset operations:
 
 | "scanConsistency"
 | ColumnarOptions.ScanConsistency
-| Valid options are "requestPlus" / ColumnarOptions.RequestPlusScanConsistency and "notBounded" / ColumnarOptions.NotBoundedScanConsistency.
+| Valid options are ,requestPlus` / `ColumnarOptions.RequestPlusScanConsistency` and `notBounded` / `ColumnarOptions.NotBoundedScanConsistency`.
 | "notBounded"
 
 | "inferLimit"
@@ -722,7 +743,7 @@ The available options for Capella Columnar DataFrame and Dataset operations:
 
 == Aggregate Push Down
 
-The following predicates are pushed down to the query, operational analytics, Enterprise Analytics, and Capella Columnar engines if possible:
+The following predicates are pushed down to the query, operational analytics, Enterprise Analytics, and Capella Analytics engines if possible:
 
 - `MIN(field)`
 - `MAX(field)`