From 6d7eb3b75642ec6e88884496c697a53a84f53a4e Mon Sep 17 00:00:00 2001
From: Simon Dew <Simon.Dew@couchbase.com>
Date: Fri, 17 Oct 2025 14:57:26 +0100
Subject: [PATCH 1/5] Update Vector Search examples

---
 .../examples/run-vector-search-generate-embed.go              | 2 +-
 .../examples/run-vector-search-generate-embed.java            | 2 +-
 .../examples/run-vector-search-generate-embed.py              | 2 +-
 .../vector-search/examples/run-vector-search-simple-color.go  | 2 +-
 .../examples/run-vector-search-simple-color.java              | 2 +-
 .../vector-search/examples/run-vector-search-simple-color.py  | 2 +-
 .../vector-search/examples/vector-search-index-payload.jsonc  | 4 ++--
 modules/vector-search/partials/download-sample-partial.adoc   | 2 +-
 8 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/modules/vector-search/examples/run-vector-search-generate-embed.go b/modules/vector-search/examples/run-vector-search-generate-embed.go
index 4894d3ead..37623b39e 100644
--- a/modules/vector-search/examples/run-vector-search-generate-embed.go
+++ b/modules/vector-search/examples/run-vector-search-generate-embed.go
@@ -74,7 +74,7 @@ func main() {
     username := os.Getenv("CB_USERNAME")
     password := os.Getenv("CB_PASSWORD")
 	// Make sure to change the bucket, and scope names to match where you stored the sample data in your database. 
-    bucket_name := "vector-sample"
+    bucket_name := "color-vector-sample"
     scope_name := "color"
 
     cluster, err := gocb.Connect(connstr, gocb.ClusterOptions{
diff --git a/modules/vector-search/examples/run-vector-search-generate-embed.java b/modules/vector-search/examples/run-vector-search-generate-embed.java
index 183d14514..af60ff3f9 100644
--- a/modules/vector-search/examples/run-vector-search-generate-embed.java
+++ b/modules/vector-search/examples/run-vector-search-generate-embed.java
@@ -67,7 +67,7 @@ public static void main(String[] args) {
 	String username = System.getenv("CB_USERNAME");
 	String password = System.getenv("CB_PASSWORD");
 // Make sure to change the bucket, scope, collection, and index names to match where you stored the sample data in your database. 
-	String bucketName = "vector-sample";
+	String bucketName = "color-vector-sample";
 	String scopeName = "color";
 	String collectionName = "rgb";
 	String searchIndexName = "color-index";
diff --git a/modules/vector-search/examples/run-vector-search-generate-embed.py b/modules/vector-search/examples/run-vector-search-generate-embed.py
index 4a80dc62c..14916721d 100644
--- a/modules/vector-search/examples/run-vector-search-generate-embed.py
+++ b/modules/vector-search/examples/run-vector-search-generate-embed.py
@@ -22,7 +22,7 @@
 pa = PasswordAuthenticator(os.getenv("CB_USERNAME"), os.getenv("CB_PASSWORD"))
 cluster = Cluster("couchbases://" + os.getenv("CB_HOSTNAME") + "/?ssl=no_verify", ClusterOptions(pa))
 # Make sure to change the bucket, scope, and index names to match where you stored the sample data in your database. 
-bucket = cluster.bucket("vector-sample")
+bucket = cluster.bucket("color-vector-sample")
 scope = bucket.scope("color")
 search_index = "color-index"
 try:
diff --git a/modules/vector-search/examples/run-vector-search-simple-color.go b/modules/vector-search/examples/run-vector-search-simple-color.go
index 9f56e35df..a3718c3a6 100644
--- a/modules/vector-search/examples/run-vector-search-simple-color.go
+++ b/modules/vector-search/examples/run-vector-search-simple-color.go
@@ -16,7 +16,7 @@ func main() {
     username := os.Getenv("CB_USERNAME")
     password := os.Getenv("CB_PASSWORD")
 	// Make sure to change the bucket, and scope names to match where you stored the sample data in your database. 
-    bucket_name := "vector-sample"
+    bucket_name := "color-vector-sample"
     scope_name := "color"
 
     cluster, err := gocb.Connect(connstr, gocb.ClusterOptions{
diff --git a/modules/vector-search/examples/run-vector-search-simple-color.java b/modules/vector-search/examples/run-vector-search-simple-color.java
index 9ff873d4d..88dfd77f0 100644
--- a/modules/vector-search/examples/run-vector-search-simple-color.java
+++ b/modules/vector-search/examples/run-vector-search-simple-color.java
@@ -18,7 +18,7 @@ public static void main(String[] args) {
 	String username = System.getenv("CB_USERNAME");
 	String password = System.getenv("CB_PASSWORD");
     // Make sure to change the bucket, scope, collection, and index names to match where you stored the sample data in your database. 
-	String bucketName = "vector-sample";
+	String bucketName = "color-vector-sample";
 	String scopeName = "color";
 	String collectionName = "rgb";
 	String searchIndexName = "color-index";
diff --git a/modules/vector-search/examples/run-vector-search-simple-color.py b/modules/vector-search/examples/run-vector-search-simple-color.py
index ee0869c13..85516c514 100644
--- a/modules/vector-search/examples/run-vector-search-simple-color.py
+++ b/modules/vector-search/examples/run-vector-search-simple-color.py
@@ -17,7 +17,7 @@
 pa = PasswordAuthenticator(os.getenv("CB_USERNAME"), os.getenv("CB_PASSWORD"))
 cluster = Cluster("couchbases://" + os.getenv("CB_HOSTNAME") + "/?ssl=no_verify", ClusterOptions(pa))
 # Make sure to change the bucket, scope, and index names to match where you stored the sample data in your database.  
-bucket = cluster.bucket("vector-sample")
+bucket = cluster.bucket("color-vector-sample")
 scope = bucket.scope("color")
 search_index = "color-index"
 try:
diff --git a/modules/vector-search/examples/vector-search-index-payload.jsonc b/modules/vector-search/examples/vector-search-index-payload.jsonc
index 5b70f0f21..7c5d47c8d 100644
--- a/modules/vector-search/examples/vector-search-index-payload.jsonc
+++ b/modules/vector-search/examples/vector-search-index-payload.jsonc
@@ -1,8 +1,8 @@
 {
   "type": "fulltext-index",
-  "name": "vector-sample.color.color-index",
+  "name": "color-vector-sample.color.color-index",
   "sourceType": "gocbcore",
-  "sourceName": "vector-sample",
+  "sourceName": "color-vector-sample",
   "planParams": {
     "maxPartitionsPerPIndex": 512,
     "indexPartitions": 1
diff --git a/modules/vector-search/partials/download-sample-partial.adoc b/modules/vector-search/partials/download-sample-partial.adoc
index 3786ab73a..8f8167ddb 100644
--- a/modules/vector-search/partials/download-sample-partial.adoc
+++ b/modules/vector-search/partials/download-sample-partial.adoc
@@ -1,4 +1,4 @@
 You can import a sample dataset to use with the procedure or examples on this page. 
 
-Go to menu:Data Tools[Import] from your cluster and xref:clusters:data-service/import-data-documents.adoc#import-sample-data[import the vector-sample] sample data.
+Go to menu:Data Tools[Import] from your cluster and xref:clusters:data-service/import-data-documents.adoc#import-sample-data[import the color-vector-sample] sample data.
 

From b8dad2a9e06ce6cf865a7f775ab16ed0b5a915c6 Mon Sep 17 00:00:00 2001
From: Simon Dew <Simon.Dew@couchbase.com>
Date: Fri, 17 Oct 2025 14:59:27 +0100
Subject: [PATCH 2/5] Update Vector Index examples

---
 .../examples/find-reranking-cases.py          |  8 +--
 .../examples/gsi-vector-idx-examples.sqlpp    | 14 ++---
 .../examples/hyperscale-idx-examples.sqlpp    | 58 +++++++++----------
 .../pages/composite-vector-index.adoc         |  6 +-
 .../pages/hyperscale-vector-index.adoc        |  6 +-
 5 files changed, 46 insertions(+), 46 deletions(-)

diff --git a/modules/vector-index/examples/find-reranking-cases.py b/modules/vector-index/examples/find-reranking-cases.py
index 30fae2822..696f60f03 100644
--- a/modules/vector-index/examples/find-reranking-cases.py
+++ b/modules/vector-index/examples/find-reranking-cases.py
@@ -12,14 +12,14 @@
 COUCHBASE_URL = "couchbase://localhost"
 USERNAME = "Administrator"
 PASSWORD = "password"
-BUCKET_NAME = "vector-sample"
+BUCKET_NAME = "color-vector-sample"
 
 # --- Connect to Cluster ---
 cluster = Cluster(COUCHBASE_URL, ClusterOptions(PasswordAuthenticator(USERNAME, PASSWORD)))
 cluster.wait_until_ready(timedelta(seconds=10))
 
 # --- Get all search-color IDs ---
-get_ids_query = "SELECT META().id AS id FROM `vector-sample`.`color`.`rgb`"
+get_ids_query = "SELECT META().id AS id FROM `color-vector-sample`.`color`.`rgb`"
 search_colors = cluster.query(get_ids_query)
 search_color_ids = [row["id"] for row in search_colors]
 
@@ -29,10 +29,10 @@ def run_vector_query(search_color_id, use_rerank=False, limit=10):
     query = f"""
     WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector  
-        FROM `vector-sample`.`color`.`rgb-questions` 
+        FROM `color-vector-sample`.`color`.`rgb-questions` 
         WHERE meta().id = "{search_color_id}")
     SELECT b.color, b.description, b.id
-    FROM `vector-sample`.`color`.`rgb` AS b
+    FROM `color-vector-sample`.`color`.`rgb` AS b
     ORDER BY APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, question_vec[0], "l2", 4, {rerank_str})
     LIMIT {limit};
     """
diff --git a/modules/vector-index/examples/gsi-vector-idx-examples.sqlpp b/modules/vector-index/examples/gsi-vector-idx-examples.sqlpp
index 700aedccf..ed5b1444b 100644
--- a/modules/vector-index/examples/gsi-vector-idx-examples.sqlpp
+++ b/modules/vector-index/examples/gsi-vector-idx-examples.sqlpp
@@ -2,7 +2,7 @@
 SELECT RAW OBJECT_PUT(d, "embedding_vector_dot",
   ARRAY_CONCAT(d.embedding_vector_dot[0:4], ["..."])
 )
-FROM `vector-sample`.`color`.`rgb` AS d
+FROM `color-vector-sample`.`color`.`rgb` AS d
 USE KEYS ["#FFEFD5"];
 /* end::get-sample-doc[] */
 
@@ -15,25 +15,25 @@ SELECT RAW OBJECT_PUT(d, "couchbase_search_query",
     FOR k IN d.couchbase_search_query.knn END
   )
 )
-FROM `vector-sample`.`color`.`rgb-questions` AS d
+FROM `color-vector-sample`.`color`.`rgb-questions` AS d
 USE KEYS ["#FFEFD5"];
 /* end::get-sample-doc-question[] */
 
 
 /* tag::create-rgb-idx[] */
-CREATE INDEX `color_vectors_idx` ON `vector-sample`.`color`.`rgb`
+CREATE INDEX `color_vectors_idx` ON `color-vector-sample`.`color`.`rgb`
        (`colorvect_l2` VECTOR, color, brightness)
        WITH {  "dimension":3 , "similarity":"L2", "description":"IVF,SQ8"};
 /* end::create-rgb-idx[] */
 
 /* tag::create-vectors-idx[] */
-CREATE INDEX `color_desc_idx` ON `vector-sample`.`color`.`rgb` 
+CREATE INDEX `color_desc_idx` ON `color-vector-sample`.`color`.`rgb` 
      (`embedding_vector_dot` VECTOR, color, brightness) 
      WITH { "dimension":1536, "similarity":"DOT", "description":" IVF,SQ8" }
 /* end::create-vectors-idx[] */
 
 /* tag::create-colors-idx[] */
-CREATE INDEX `color_name_idx` ON `vector-sample`.`color`.`rgb`
+CREATE INDEX `color_name_idx` ON `color-vector-sample`.`color`.`rgb`
      (color, brightness, `embedding_vector_dot` VECTOR)
      WITH { "dimension":1536, "similarity":"DOT", "description":" IVF,SQ8" }
 /* end::create-colors-idx[] */
@@ -54,7 +54,7 @@ LIMIT 5;
 /* tag::query-vectors-idx-subquery[] */
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector  
-        from `vector-sample`.`color`.`rgb-questions` 
+        from `color-vector-sample`.`color`.`rgb-questions` 
         WHERE meta().id = "#FFEFD5")
 SELECT b.color, b.description from `rgb` AS b 
 order by APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, 
@@ -64,7 +64,7 @@ question_vec[0], "DOT")  LIMIT 3;
 /* tag::query-vectors-idx-subquery-filtered[] */
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector  
-        from `vector-sample`.`color`.`rgb-questions` 
+        from `color-vector-sample`.`color`.`rgb-questions` 
         WHERE meta().id = "#FFEFD5")
 SELECT b.color, b.description, b.brightness from `rgb` AS b 
 WHERE b.brightness > 190.0
diff --git a/modules/vector-index/examples/hyperscale-idx-examples.sqlpp b/modules/vector-index/examples/hyperscale-idx-examples.sqlpp
index ba9637253..2203262a5 100644
--- a/modules/vector-index/examples/hyperscale-idx-examples.sqlpp
+++ b/modules/vector-index/examples/hyperscale-idx-examples.sqlpp
@@ -1,6 +1,6 @@
 /* tag::create-rgb-idx[] */
 CREATE VECTOR INDEX `color_desc_hyperscale` 
-       ON `vector-sample`.`color`.`rgb`(`embedding_vector_dot` VECTOR)
+       ON `color-vector-sample`.`color`.`rgb`(`embedding_vector_dot` VECTOR)
        WITH { "dimension":1536, "similarity":"L2", "description":"IVF8,SQ4" }
 /* end::create-rgb-idx[] */
 
@@ -14,7 +14,7 @@ SELECT
     d.embedding_vector_dot[0:4], 
     ["..."]
   ) AS embedding_vector_dot
-FROM `vector-sample`.`color`.`rgb` AS d
+FROM `color-vector-sample`.`color`.`rgb` AS d
 WHERE d.id = "#87CEEB";
 /* end::rgb-entry[] */
 
@@ -28,28 +28,28 @@ SELECT
     d.couchbase_search_query.knn[0].vector[0:4], 
     ["..."]
   ) AS vector
-FROM `vector-sample`.`color`.`rgb-questions` AS d
+FROM `color-vector-sample`.`color`.`rgb-questions` AS d
 WHERE d.id = "#87CEEB";
 /* end::query-rgb-questions[] */
 
 /* tag::query-rgb-with-subquery[] */
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector  
-        FROM `vector-sample`.`color`.`rgb-questions` 
+        FROM `color-vector-sample`.`color`.`rgb-questions` 
         WHERE meta().id = "#87CEEB"),
     question_answer AS (
         SELECT wanted_similar_color_from_search
-        FROM `vector-sample`.`color`.`rgb-questions` 
+        FROM `color-vector-sample`.`color`.`rgb-questions` 
         WHERE meta().id = "#87CEEB")
 SELECT b.color, b.description, q.wanted_similar_color_from_search  
-       FROM `vector-sample`.`color`.`rgb` AS b, question_answer as q
+       FROM `color-vector-sample`.`color`.`rgb` AS b, question_answer as q
        ORDER BY APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, 
        question_vec[0], "l2", 4)  LIMIT 3;
 /* end::query-rgb-with-subquery[] */
 
 /* tag::create-idx-brightness[] */
 CREATE VECTOR INDEX `color_desc_hyperscale_brightness` 
-       ON `vector-sample`.`color`.`rgb`(`embedding_vector_dot` VECTOR)
+       ON `color-vector-sample`.`color`.`rgb`(`embedding_vector_dot` VECTOR)
        INCLUDE (`brightness`)
        WITH { "dimension":1536, "similarity":"L2", "description":"IVF8,SQ4" }
 /* end::create-idx-brightness[] */
@@ -57,10 +57,10 @@ CREATE VECTOR INDEX `color_desc_hyperscale_brightness`
 /* tag::query-rgb-with-brightness[] */
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector  
-        FROM `vector-sample`.`color`.`rgb-questions` 
+        FROM `color-vector-sample`.`color`.`rgb-questions` 
         WHERE meta().id = "#87CEEB")
 SELECT b.color, b.description, b.brightness
-       FROM `vector-sample`.`color`.`rgb` AS b
+       FROM `color-vector-sample`.`color`.`rgb` AS b
        WHERE b.brightness > 170.0
        ORDER BY APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, 
        question_vec[0], "l2", 4)  LIMIT 3;
@@ -68,7 +68,7 @@ SELECT b.color, b.description, b.brightness
 
 /* tag::create-rgb-no-persist[] */
 CREATE VECTOR INDEX `color_desc_hyperscale_no_persist` 
-       ON `vector-sample`.`color`.`rgb`(`embedding_vector_dot` VECTOR)
+       ON `color-vector-sample`.`color`.`rgb`(`embedding_vector_dot` VECTOR)
        WITH { "dimension":1536, "similarity":"L2", "description":"IVF8,SQ4", 
               "persist_full_vector": false};
 /* end::create-rgb-no-persist[] */
@@ -76,10 +76,10 @@ CREATE VECTOR INDEX `color_desc_hyperscale_no_persist`
 /* tag::rerank-before-example[] */
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector  
-        FROM `vector-sample`.`color`.`rgb-questions` 
+        FROM `color-vector-sample`.`color`.`rgb-questions` 
         WHERE meta().id = "#FFFFE0")
     SELECT b.color, b.description, b.id
-    FROM `vector-sample`.`color`.`rgb` AS b
+    FROM `color-vector-sample`.`color`.`rgb` AS b
     ORDER BY APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, question_vec[0], "l2", 4)
     LIMIT 3;
 /* end::rerank-before-example[] */
@@ -87,10 +87,10 @@ WITH question_vec AS (
 /* tag::rerank-after-example[] */
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector  
-        FROM `vector-sample`.`color`.`rgb-questions` 
+        FROM `color-vector-sample`.`color`.`rgb-questions` 
         WHERE meta().id = "#FFFFE0")
     SELECT b.color, b.description, b.id
-    FROM `vector-sample`.`color`.`rgb` AS b
+    FROM `color-vector-sample`.`color`.`rgb` AS b
     ORDER BY APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, question_vec[0], "l2", 4, TRUE)
     LIMIT 3;
 /* end::rerank-after-example[] */
@@ -99,14 +99,14 @@ WITH question_vec AS (
 /* tag::query-rgb-with-distance[] */
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector  
-        FROM `vector-sample`.`color`.`rgb-questions` 
+        FROM `color-vector-sample`.`color`.`rgb-questions` 
         WHERE meta().id = "#87CEEB"),
     question_answer AS (
         SELECT wanted_similar_color_from_search
-        FROM `vector-sample`.`color`.`rgb-questions` 
+        FROM `color-vector-sample`.`color`.`rgb-questions` 
         WHERE meta().id = "#87CEEB")
 SELECT b.color, b.description, q.wanted_similar_color_from_search, approx_distance  
-       FROM `vector-sample`.`color`.`rgb` AS b, question_answer as q, 
+       FROM `color-vector-sample`.`color`.`rgb` AS b, question_answer as q, 
        APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, question_vec[0], "l2", 4) 
        as approx_distance
        ORDER BY approx_distance  LIMIT 3;
@@ -115,12 +115,12 @@ SELECT b.color, b.description, q.wanted_similar_color_from_search, approx_distan
 /* tag::untuned-query[] */
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector 
-        FROM `vector-sample`.`color`.`rgb-questions` 
+        FROM `color-vector-sample`.`color`.`rgb-questions` 
         WHERE meta().id = "#87CEEB"
     ), 
 colors AS (
     SELECT b.color
-    FROM `vector-sample`.`color`.`rgb` AS b
+    FROM `color-vector-sample`.`color`.`rgb` AS b
     ORDER BY APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, question_vec[0], "l2")
     LIMIT 10 )
 SELECT RAW colors;
@@ -130,12 +130,12 @@ SELECT RAW colors;
 /* tag::exact-query[] */
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector 
-        FROM `vector-sample`.`color`.`rgb-questions` 
+        FROM `color-vector-sample`.`color`.`rgb-questions` 
         WHERE meta().id = "#87CEEB"
     ), 
 colors AS (
     SELECT b.color
-    FROM `vector-sample`.`color`.`rgb` AS b
+    FROM `color-vector-sample`.`color`.`rgb` AS b
     ORDER BY VECTOR_DISTANCE(b.embedding_vector_dot, question_vec[0], "l2")
     LIMIT 10 )
 SELECT RAW colors;
@@ -145,20 +145,20 @@ SELECT RAW colors;
 -- Get the vector for the question
 WITH question_vec AS (
     SELECT RAW couchbase_search_query.knn[0].vector
-    FROM `vector-sample`.`color`.`rgb-questions`
+    FROM `color-vector-sample`.`color`.`rgb-questions`
     WHERE meta().id = "#87CEEB"
 ),
 -- Exact Search results
 GroundTruthResults AS (
     SELECT b.color
-    FROM `vector-sample`.`color`.`rgb` AS b
+    FROM `color-vector-sample`.`color`.`rgb` AS b
     ORDER BY VECTOR_DISTANCE(b.embedding_vector_dot,
     question_vec[0], "l2") LIMIT 10
 ),
 -- Approximate Search results
 ApproximateResults AS (
     SELECT b.color
-    FROM `vector-sample`.`color`.`rgb` AS b
+    FROM `color-vector-sample`.`color`.`rgb` AS b
     ORDER BY APPROX_VECTOR_DISTANCE(b.embedding_vector_dot,
     question_vec[0], "l2") LIMIT 10
 )
@@ -182,20 +182,20 @@ LEFT JOIN
 -- Get the vector for the question
 WITH question_vec AS (
     SELECT RAW couchbase_search_query.knn[0].vector
-    FROM `vector-sample`.`color`.`rgb-questions`
+    FROM `color-vector-sample`.`color`.`rgb-questions`
     WHERE meta().id = "#87CEEB"
 ),
 -- Exact Search results
 GroundTruthResults AS (
     SELECT b.color
-    FROM `vector-sample`.`color`.`rgb` AS b
+    FROM `color-vector-sample`.`color`.`rgb` AS b
     ORDER BY VECTOR_DISTANCE(b.embedding_vector_dot,
     question_vec[0], "l2") LIMIT 10
 ),
 -- Approximate Search results, this timw with nProbes set to 4:
 ApproximateResults AS (
     SELECT b.color
-    FROM `vector-sample`.`color`.`rgb` AS b
+    FROM `color-vector-sample`.`color`.`rgb` AS b
     ORDER BY APPROX_VECTOR_DISTANCE(b.embedding_vector_dot,
     question_vec[0], "l2", 4) LIMIT 10
 )
@@ -219,12 +219,12 @@ LEFT JOIN
 /* tag::tuned-query[] */
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector 
-        FROM `vector-sample`.`color`.`rgb-questions` 
+        FROM `color-vector-sample`.`color`.`rgb-questions` 
         WHERE meta().id = "#87CEEB"
     ), 
 colors AS (
     SELECT b.color
-    FROM `vector-sample`.`color`.`rgb` AS b
+    FROM `color-vector-sample`.`color`.`rgb` AS b
     ORDER BY APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, question_vec[0], "l2", 4)
     LIMIT 10 )
 SELECT RAW colors;
diff --git a/modules/vector-index/pages/composite-vector-index.adoc b/modules/vector-index/pages/composite-vector-index.adoc
index 7204c06b2..74e44a567 100644
--- a/modules/vector-index/pages/composite-vector-index.adoc
+++ b/modules/vector-index/pages/composite-vector-index.adoc
@@ -98,7 +98,7 @@ include::partial$index-algorithm-settings.adoc[]
 The following examples show you how to create two Composite Vector index with a vector column using sample data.
 They both use the data from the `color_data_2vectors.zip` file mentioned earlier.
 
-The following query gets a single document from the `rgb` collection in the `vector-sample` bucket's `color` scope.
+The following query gets a single document from the `rgb` collection in the `color-vector-sample` bucket's `color` scope.
 It truncates the `embedding_vector_dot` attribute to the first four values to improve readability.
 
 [source,sqlpp]
@@ -366,7 +366,7 @@ In a production environment, your application calls the same embedding model it
 
 For this example, you can use embedded vectors in the `rgb_questions.json` file that's in the `color_data_2vectors.zip` file.
 This file contains a `question` attribute containing a search prompt for a particular color.
-The following query gets a single document from the `rgb_questions` collection in the `vector-sample` bucket's `color` scope.
+The following query gets a single document from the `rgb_questions` collection in the `color-vector-sample` bucket's `color` scope.
 It truncates the `couchbase_search_query.knn.vector` attribute to the first four values to improve readability.
 
 [source,sqlpp]
@@ -394,7 +394,7 @@ include::vector-index:example$query-vectors-idx-whole.sqlpp[tags=!query-vectors-
 
 Click btn:[icon:github[\] View] to see and copy the entire query with all the vectors.
 
-Another option is to import the `rgb_questions.json` file into another collection in the `vector-sample` bucket's `color` scope named `rgb-questions`.
+Another option is to import the `rgb_questions.json` file into another collection in the `color-vector-sample` bucket's `color` scope named `rgb-questions`.
 Then you can use a subquery to get the vectors for the question and use it in your query of the `rgb` collection's `embedding_vector_dot` attribute:
 
 [source,sqlpp]
diff --git a/modules/vector-index/pages/hyperscale-vector-index.adoc b/modules/vector-index/pages/hyperscale-vector-index.adoc
index b213bd327..b9472913c 100644
--- a/modules/vector-index/pages/hyperscale-vector-index.adoc
+++ b/modules/vector-index/pages/hyperscale-vector-index.adoc
@@ -117,7 +117,7 @@ There's also a field named `couchbase_search_query.knn.vector` that contains an
 
 include::vector-search:partial$download-sample-partial.adoc[]
 
-The following query returns a sample document from the data in the `vector-sample.color.rgb` collection, truncating the embedded vector to 4 values to make the result readable:
+The following query returns a sample document from the data in the `color-vector-sample.color.rgb` collection, truncating the embedded vector to 4 values to make the result readable:
 
 [source,sqlpp]
 ----
@@ -205,7 +205,7 @@ You must supply a vector value in your query that Couchbase {product-name} can c
 In actual use, your application generates a vector for the query value using the same embedding model it used to embed the vectors in your documents.
 
 To avoid the complication of calling an embedding model, this example uses embedded vectors in the `rgb_questions.json` file that's included in `color_data_2vectors.zip`.
-For this example, the contents of this file are loaded into a collection named `vector-sample.color.rgb-questions`.
+For this example, the contents of this file are loaded into a collection named `color-vector-sample.color.rgb-questions`.
 This collection contains a `question` attribute which is a search prompt for a particular color.
 The `couchbase_search_query.knn.vector` attribute contains the embedded vector for the `question` attribute.
 The following query lists several attributes from a document in the collection.
@@ -224,7 +224,7 @@ include::vector-index:example$hyperscale-idx-data.json[tag=query-rgb-questions-o
 ----
 
 To use the embedded vector, you need to include the `couchbase_search_query.knn.vector` attribute in your query's `SELECT` statement.
-You can either directly copy and paste the entire array into your query or use a subquery to retrieve it from the `vector-sample.color.rgb-questions` collection.
+You can either directly copy and paste the entire array into your query or use a subquery to retrieve it from the `color-vector-sample.color.rgb-questions` collection.
 The following example uses a subquery to get the vector, and also includes the `wanted_similar_color_from_search` attribute in the output which shows you the color that the query should return.
 
 [source,sqlpp]

From 73d0204db97a4df413ab72cf61cfac95799e0405 Mon Sep 17 00:00:00 2001
From: Simon Dew <Simon.Dew@couchbase.com>
Date: Fri, 17 Oct 2025 15:00:30 +0100
Subject: [PATCH 3/5] Update Query examples

---
 .../pages/n1ql-language-reference/altervectorindex.adoc     | 4 ++--
 modules/n1ql/pages/n1ql-language-reference/createindex.adoc | 6 +++---
 .../pages/n1ql-language-reference/createvectorindex.adoc    | 2 +-
 .../n1ql/pages/n1ql-language-reference/dropvectorindex.adoc | 6 +++---
 modules/n1ql/pages/n1ql-language-reference/vectorfun.adoc   | 2 +-
 5 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/modules/n1ql/pages/n1ql-language-reference/altervectorindex.adoc b/modules/n1ql/pages/n1ql-language-reference/altervectorindex.adoc
index 3e88a6132..18a6da352 100644
--- a/modules/n1ql/pages/n1ql-language-reference/altervectorindex.adoc
+++ b/modules/n1ql/pages/n1ql-language-reference/altervectorindex.adoc
@@ -58,9 +58,9 @@ To try the examples in this section, you must do the following:
 The examples in this section assume that the 3 nodes have the names `svc-dqi-node-001`, `svc-dqi-node-002`, and `svc-dqi-node-003`.
 The nodes in your cluster may have different names or IP addresses.
 
-. Install the vector sample data as described in {prerequisites}[Prerequisites].
+. Install the `color-vector-sample` data as described in {prerequisites}[Prerequisites].
 
-. Set the query context to the `color` scope in the vector sample dataset.
+. Set the query context to the `color` scope in the `color-vector-sample` dataset.
 For more information, see xref:n1ql:n1ql-intro/queriesandresults.adoc#query-context[Query Context].
 
 .Create and move an index from one node to another
diff --git a/modules/n1ql/pages/n1ql-language-reference/createindex.adoc b/modules/n1ql/pages/n1ql-language-reference/createindex.adoc
index 80bd0e264..082b626c2 100644
--- a/modules/n1ql/pages/n1ql-language-reference/createindex.adoc
+++ b/modules/n1ql/pages/n1ql-language-reference/createindex.adoc
@@ -722,7 +722,7 @@ For more examples of indexes where the leading key may be missing, see xref:n1ql
 [[ex-create-rgb-idx]]
 .Create a Composite Vector index
 ====
-For this example, you must install the vector sample data as described in {prerequisites}[Prerequisites].
+For this example, you must install the `color-vector-sample` data as described in {prerequisites}[Prerequisites].
 The path to the required keyspace is specified by the query, so you do not need to set the query context.
 
 Create a Composite Vector index that indexes the vector field named `colorvect_l2`, as well as the scalar `color` and `brightness` fields.
@@ -736,7 +736,7 @@ include::vector-index:example$gsi-vector-idx-examples.sqlpp[tag=create-rgb-idx]
 [[ex-create-vectors-idx]]
 .Create a Composite Vector index using embedded vectors
 ====
-For this example, you must install the vector sample data as described in {prerequisites}[Prerequisites].
+For this example, you must install the `color-vector-sample` data as described in {prerequisites}[Prerequisites].
 The path to the required keyspace is specified by the query, so you do not need to set the query context.
 
 Create a Composite Vector index that indexes the vector field named `embedding-vector-dot`, as well as the scalar `color` and `brightness` fields.
@@ -750,7 +750,7 @@ include::vector-index:example$gsi-vector-idx-examples.sqlpp[tag=create-vectors-i
 [[ex-create-colors-idx]]
 .Create a Composite Vector index with a scalar leading key
 ====
-For this example, you must install the vector sample data as described in {prerequisites}[Prerequisites].
+For this example, you must install the `color-vector-sample` data as described in {prerequisites}[Prerequisites].
 The path to the required keyspace is specified by the query, so you do not need to set the query context.
 
 Create a Composite Vector index that indexes the scalar `color` and `brightness` fields, as well as the vector field named `embedding-vector-dot`.
diff --git a/modules/n1ql/pages/n1ql-language-reference/createvectorindex.adoc b/modules/n1ql/pages/n1ql-language-reference/createvectorindex.adoc
index babcd9665..491454051 100644
--- a/modules/n1ql/pages/n1ql-language-reference/createvectorindex.adoc
+++ b/modules/n1ql/pages/n1ql-language-reference/createvectorindex.adoc
@@ -175,7 +175,7 @@ include::createindex.adoc[tags=defer-index-builds-by-default]
 
 == Examples
 
-To try the examples in this section, you must install the vector sample data as described in {prerequisites}[Prerequisites].
+To try the examples in this section, you must install the `color-vector-sample` data as described in {prerequisites}[Prerequisites].
 
 [[ex-create-rgb-idx]]
 .Create a Hyperscale Vector index
diff --git a/modules/n1ql/pages/n1ql-language-reference/dropvectorindex.adoc b/modules/n1ql/pages/n1ql-language-reference/dropvectorindex.adoc
index 56673a954..3faf03854 100644
--- a/modules/n1ql/pages/n1ql-language-reference/dropvectorindex.adoc
+++ b/modules/n1ql/pages/n1ql-language-reference/dropvectorindex.adoc
@@ -49,7 +49,7 @@ include::dropindex.adoc[tags=usage]
 
 == Examples
 
-To try the examples in this section, you must install the vector sample data as described in {prerequisites}[Prerequisites].
+To try the examples in this section, you must install the `color-vector-sample` data as described in {prerequisites}[Prerequisites].
 
 [[ex-1]]
 .Drop a Hyperscale Vector index
@@ -62,7 +62,7 @@ Drop the Hyperscale Vector index called `color_desc_hyperscale`, if it exists.
 ----
 DROP VECTOR INDEX `color_desc_hyperscale`
      IF EXISTS
-     ON `vector-sample`.color.rgb
+     ON `color-vector-sample`.color.rgb
 ----
 
 The following command would drop the index in exactly the same way, but uses alternative syntax.
@@ -70,7 +70,7 @@ The following command would drop the index in exactly the same way, but uses alt
 [source,sqlpp]
 ----
 DROP VECTOR INDEX IF EXISTS
-     default:`vector-sample`.color.rgb.`color_desc_hyperscale`
+     default:`color-vector-sample`.color.rgb.`color_desc_hyperscale`
 ----
 ====
 
diff --git a/modules/n1ql/pages/n1ql-language-reference/vectorfun.adoc b/modules/n1ql/pages/n1ql-language-reference/vectorfun.adoc
index 7d62cc8ba..dee57e169 100644
--- a/modules/n1ql/pages/n1ql-language-reference/vectorfun.adoc
+++ b/modules/n1ql/pages/n1ql-language-reference/vectorfun.adoc
@@ -457,7 +457,7 @@ Check whether the specified fields in the `rgb` collection contain vector values
 SELECT ISVECTOR(description, 1, "float32") AS description,
        ISVECTOR(colorvect_l2, 3, "float32") AS colorvect_l2,
        ISVECTOR(embedding_vector_dot, 1536, "float32") AS embedding_vector_dot
-FROM `vector-sample`.color.rgb LIMIT 1;
+FROM `color-vector-sample`.color.rgb LIMIT 1;
 ----
 
 .Results

From 4aa610e23824d33f21d0719979447a68b9b2fe86 Mon Sep 17 00:00:00 2001
From: Simon Dew <Simon.Dew@couchbase.com>
Date: Fri, 17 Oct 2025 17:30:09 +0100
Subject: [PATCH 4/5] Update examples for Hyperscale Vector indexes

---
 .../examples/hyperscale-idx-examples.sqlpp    | 33 +++++++++----------
 .../pages/hyperscale-vector-index.adoc        | 19 ++++++++---
 .../pages/vector-index-best-practices.adoc    |  3 ++
 3 files changed, 33 insertions(+), 22 deletions(-)

diff --git a/modules/vector-index/examples/hyperscale-idx-examples.sqlpp b/modules/vector-index/examples/hyperscale-idx-examples.sqlpp
index 2203262a5..6275d04d0 100644
--- a/modules/vector-index/examples/hyperscale-idx-examples.sqlpp
+++ b/modules/vector-index/examples/hyperscale-idx-examples.sqlpp
@@ -15,7 +15,7 @@ SELECT
     ["..."]
   ) AS embedding_vector_dot
 FROM `color-vector-sample`.`color`.`rgb` AS d
-WHERE d.id = "#87CEEB";
+USE KEYS "87CEEB";
 /* end::rgb-entry[] */
 
 
@@ -29,18 +29,18 @@ SELECT
     ["..."]
   ) AS vector
 FROM `color-vector-sample`.`color`.`rgb-questions` AS d
-WHERE d.id = "#87CEEB";
+USE KEYS "#87CEEB";
 /* end::query-rgb-questions[] */
 
 /* tag::query-rgb-with-subquery[] */
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector  
         FROM `color-vector-sample`.`color`.`rgb-questions` 
-        WHERE meta().id = "#87CEEB"),
+        USE KEYS "#87CEEB"),
     question_answer AS (
         SELECT wanted_similar_color_from_search
         FROM `color-vector-sample`.`color`.`rgb-questions` 
-        WHERE meta().id = "#87CEEB")
+        USE KEYS "#87CEEB")
 SELECT b.color, b.description, q.wanted_similar_color_from_search  
        FROM `color-vector-sample`.`color`.`rgb` AS b, question_answer as q
        ORDER BY APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, 
@@ -58,7 +58,7 @@ CREATE VECTOR INDEX `color_desc_hyperscale_brightness`
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector  
         FROM `color-vector-sample`.`color`.`rgb-questions` 
-        WHERE meta().id = "#87CEEB")
+        USE KEYS "#87CEEB")
 SELECT b.color, b.description, b.brightness
        FROM `color-vector-sample`.`color`.`rgb` AS b
        WHERE b.brightness > 170.0
@@ -77,7 +77,7 @@ CREATE VECTOR INDEX `color_desc_hyperscale_no_persist`
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector  
         FROM `color-vector-sample`.`color`.`rgb-questions` 
-        WHERE meta().id = "#FFFFE0")
+        USE KEYS "#FFFFE0")
     SELECT b.color, b.description, b.id
     FROM `color-vector-sample`.`color`.`rgb` AS b
     ORDER BY APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, question_vec[0], "l2", 4)
@@ -88,7 +88,7 @@ WITH question_vec AS (
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector  
         FROM `color-vector-sample`.`color`.`rgb-questions` 
-        WHERE meta().id = "#FFFFE0")
+        USE KEYS "#FFFFE0")
     SELECT b.color, b.description, b.id
     FROM `color-vector-sample`.`color`.`rgb` AS b
     ORDER BY APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, question_vec[0], "l2", 4, TRUE)
@@ -100,15 +100,14 @@ WITH question_vec AS (
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector  
         FROM `color-vector-sample`.`color`.`rgb-questions` 
-        WHERE meta().id = "#87CEEB"),
+        USE KEYS "#87CEEB"),
     question_answer AS (
         SELECT wanted_similar_color_from_search
         FROM `color-vector-sample`.`color`.`rgb-questions` 
-        WHERE meta().id = "#87CEEB")
+        USE KEYS "#87CEEB")
 SELECT b.color, b.description, q.wanted_similar_color_from_search, approx_distance  
-       FROM `color-vector-sample`.`color`.`rgb` AS b, question_answer as q, 
-       APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, question_vec[0], "l2", 4) 
-       as approx_distance
+       FROM `color-vector-sample`.`color`.`rgb` AS b, question_answer as q 
+       LET approx_distance = APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, question_vec[0], "l2", 4) 
        ORDER BY approx_distance  LIMIT 3;
 /* end::query-rgb-with-distance[] */
 
@@ -116,7 +115,7 @@ SELECT b.color, b.description, q.wanted_similar_color_from_search, approx_distan
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector 
         FROM `color-vector-sample`.`color`.`rgb-questions` 
-        WHERE meta().id = "#87CEEB"
+        USE KEYS "#87CEEB"
     ), 
 colors AS (
     SELECT b.color
@@ -131,7 +130,7 @@ SELECT RAW colors;
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector 
         FROM `color-vector-sample`.`color`.`rgb-questions` 
-        WHERE meta().id = "#87CEEB"
+        USE KEYS "#87CEEB"
     ), 
 colors AS (
     SELECT b.color
@@ -146,7 +145,7 @@ SELECT RAW colors;
 WITH question_vec AS (
     SELECT RAW couchbase_search_query.knn[0].vector
     FROM `color-vector-sample`.`color`.`rgb-questions`
-    WHERE meta().id = "#87CEEB"
+    USE KEYS "#87CEEB"
 ),
 -- Exact Search results
 GroundTruthResults AS (
@@ -183,7 +182,7 @@ LEFT JOIN
 WITH question_vec AS (
     SELECT RAW couchbase_search_query.knn[0].vector
     FROM `color-vector-sample`.`color`.`rgb-questions`
-    WHERE meta().id = "#87CEEB"
+    USE KEYS "#87CEEB"
 ),
 -- Exact Search results
 GroundTruthResults AS (
@@ -220,7 +219,7 @@ LEFT JOIN
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector 
         FROM `color-vector-sample`.`color`.`rgb-questions` 
-        WHERE meta().id = "#87CEEB"
+        USE KEYS "#87CEEB"
     ), 
 colors AS (
     SELECT b.color
diff --git a/modules/vector-index/pages/hyperscale-vector-index.adoc b/modules/vector-index/pages/hyperscale-vector-index.adoc
index b9472913c..2ec05b5bd 100644
--- a/modules/vector-index/pages/hyperscale-vector-index.adoc
+++ b/modules/vector-index/pages/hyperscale-vector-index.adoc
@@ -63,6 +63,17 @@ See xref:vector-index:vectors-and-indexes-overview.adoc#vector_similarity[Vector
 
 include::vector-search:partial$download-sample-partial.adoc[]
 
+In addition, to get the best results with the examples on this page, download the following sample dataset:
+
+https://cbc-remote-execution-examples-prod.s3.amazonaws.com/color_data_2vectors.zip[Download color_data_2vectors.zip]
+
+When you have downloaded `color_data_2vectors.zip`, unzip it, then xref:guides:load.adoc[import] the `rgb_questions.json` file with the following settings:
+
+* Use the `color-vector-sample` bucket.
+* Use the `color` scope.
+* Create a new target collection called `rgb-questions` -- with a hyphen `-`, not an underscore `&lowbar;`.
+* To set your document keys, use the value of the `id` field from the JSON document.
+
 [#create-index]
 
 include::vector-index:partial$create-hyperscale-index-capella-ui.adoc[opts=optional]
@@ -112,10 +123,8 @@ include::partial$index-algorithm-settings.adoc[]
 [#examples]
 === Create Hyperscale Vector Index Example
 
-The examples in this section use a dataset that contains information about colors including a text description of the color.
-There's also a field named `couchbase_search_query.knn.vector` that contains an embedded vector for the color description.
-
-include::vector-search:partial$download-sample-partial.adoc[]
+The examples in this section use the `color-vector-sample.color.rgb` collection.
+This contains information about colors, including a text description of the color.
 
 The following query returns a sample document from the data in the `color-vector-sample.color.rgb` collection, truncating the embedded vector to 4 values to make the result readable:
 
@@ -132,7 +141,7 @@ The result of running the query is:
 include::vector-index:example$hyperscale-idx-data.json[tag=rgb-document]
 ----
 
-The following example creates an Hyperscale vector index for the vector column named `embedding-vector-dot`.
+The following example creates an Hyperscale Vector index for the vector column named `embedding-vector-dot`.
 
 [source,sqlpp]
 ----
diff --git a/modules/vector-index/pages/vector-index-best-practices.adoc b/modules/vector-index/pages/vector-index-best-practices.adoc
index 84b93e85a..a0ab8175a 100644
--- a/modules/vector-index/pages/vector-index-best-practices.adoc
+++ b/modules/vector-index/pages/vector-index-best-practices.adoc
@@ -210,6 +210,9 @@ The following example uses the `VECTOR_DISTANCE` function instead of the `APPROX
 include::vector-index:example$hyperscale-idx-examples.sqlpp[tag=exact-query]
 ----
 
+TIP: If the query fails and Couchbase Capella advises you to create a primary index, click btn:[Build Primary Index].
+When the primary index is created, run the query again.
+
 Running the query returns the following results:
 
 [source,json]

From 595888e7dc3ec21cbdf81843e1bbae98f8f3efbe Mon Sep 17 00:00:00 2001
From: Simon Dew <Simon.Dew@couchbase.com>
Date: Fri, 17 Oct 2025 17:43:57 +0100
Subject: [PATCH 5/5] Update examples for Composite Vector indexes

---
 .../examples/gsi-vector-idx-examples.sqlpp        |  6 +++---
 .../pages/composite-vector-index.adoc             | 15 ++++++++++++++-
 2 files changed, 17 insertions(+), 4 deletions(-)

diff --git a/modules/vector-index/examples/gsi-vector-idx-examples.sqlpp b/modules/vector-index/examples/gsi-vector-idx-examples.sqlpp
index ed5b1444b..7c16ec672 100644
--- a/modules/vector-index/examples/gsi-vector-idx-examples.sqlpp
+++ b/modules/vector-index/examples/gsi-vector-idx-examples.sqlpp
@@ -3,7 +3,7 @@ SELECT RAW OBJECT_PUT(d, "embedding_vector_dot",
   ARRAY_CONCAT(d.embedding_vector_dot[0:4], ["..."])
 )
 FROM `color-vector-sample`.`color`.`rgb` AS d
-USE KEYS ["#FFEFD5"];
+USE KEYS ["FFEFD5"];
 /* end::get-sample-doc[] */
 
 /* tag::get-sample-doc-question[] */
@@ -55,7 +55,7 @@ LIMIT 5;
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector  
         from `color-vector-sample`.`color`.`rgb-questions` 
-        WHERE meta().id = "#FFEFD5")
+        USE KEYS "#FFEFD5")
 SELECT b.color, b.description from `rgb` AS b 
 order by APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, 
 question_vec[0], "DOT")  LIMIT 3;
@@ -65,7 +65,7 @@ question_vec[0], "DOT")  LIMIT 3;
 WITH question_vec AS (
         SELECT RAW couchbase_search_query.knn[0].vector  
         from `color-vector-sample`.`color`.`rgb-questions` 
-        WHERE meta().id = "#FFEFD5")
+        USE KEYS "#FFEFD5")
 SELECT b.color, b.description, b.brightness from `rgb` AS b 
 WHERE b.brightness > 190.0
 order by APPROX_VECTOR_DISTANCE(b.embedding_vector_dot, 
diff --git a/modules/vector-index/pages/composite-vector-index.adoc b/modules/vector-index/pages/composite-vector-index.adoc
index 74e44a567..28da9baf2 100644
--- a/modules/vector-index/pages/composite-vector-index.adoc
+++ b/modules/vector-index/pages/composite-vector-index.adoc
@@ -52,6 +52,19 @@ See xref:vector-index:vectors-and-indexes-overview.adoc#vector_similarity[Vector
 
 include::vector-search:partial$download-sample-partial.adoc[]
 
+include::vector-search:partial$download-sample-partial.adoc[]
+
+In addition, to get the best results with the examples on this page, download the following sample dataset:
+
+https://cbc-remote-execution-examples-prod.s3.amazonaws.com/color_data_2vectors.zip[Download color_data_2vectors.zip]
+
+When you have downloaded `color_data_2vectors.zip`, unzip it, then xref:guides:load.adoc[import] the `rgb_questions.json` file with the following settings:
+
+* Use the `color-vector-sample` bucket.
+* Use the `color` scope.
+* Create a new target collection called `rgb-questions` -- with a hyphen `-`, not an underscore `&lowbar;`.
+* To set your document keys, use the value of the `id` field from the JSON document.
+
 [#create-index]
 
 include::vector-index:partial$create-composite-index-capella-ui.adoc[opts=optional]
@@ -115,7 +128,7 @@ include::vector-index:example$composite-vector-data.json[tag=sample-doc]
 
 ==== Index the RGB Values
 
-The `rgb.json` file's `colorvect_l2` attribute defines an array containing the RGB values for the entry's color.
+The `rgb` collection's `colorvect_l2` attribute defines an array containing the RGB values for the entry's color.
 While this technically is not an embedded vector, you can still create a vector index column for this array.
 The following example creates a Composite Vector index for this attribute as an embedded vector as well as the color's name and brightness.