update BigTable to Bigtable for non-yaml related files

.github/workflows/beam_StressTests_Java_BigTableIO.yml

@@ -73,7 +73,7 @@ jobs:
           github_job: ${{ matrix.job_name }} (${{ matrix.job_phrase }})
       - name: Setup environment
         uses: ./.github/actions/setup-environment-action
-      - name: run BigTable StressTest Large
+      - name: run Bigtable StressTest Large
         uses: ./.github/actions/gradle-command-self-hosted-action
         with:
           gradle-command: :it:google-cloud-platform:BigTableStressTestLarge --info -DinfluxHost="http://10.128.0.96:8086" -DinfluxDatabase="beam_test_metrics" -DinfluxMeasurement="java_stress_test_bigtable"

.test-infra/tools/refresh_looker_metrics.py

@@ -30,8 +30,8 @@
 LOOKS_TO_DOWNLOAD = [
     ("30", ["18", "50", "92", "49", "91"]),    # BigQueryIO_Read
     ("31", ["19", "52", "88", "51", "87"]),    # BigQueryIO_Write
-    ("32", ["20", "60", "104", "59", "103"]),  # BigTableIO_Read
-    ("33", ["21", "70", "116", "69", "115"]),  # BigTableIO_Write
+    ("32", ["20", "60", "104", "59", "103"]),  # BigtableIO_Read
+    ("33", ["21", "70", "116", "69", "115"]),  # BigtableIO_Write
     ("34", ["22", "56", "96", "55", "95"]),    # TextIO_Read
     ("35", ["23", "64", "110", "63", "109"]),  # TextIO_Write
     ("113", ["386", "388", "390", "392", "394"]),    # IcebergIO_Read

examples/java/src/main/java/org/apache/beam/examples/complete/datatokenization/DataTokenization.java

@@ -78,7 +78,7 @@
  *       <ul>
  *         <li>File system (Only JSON or CSV)
  *         <li><a href=https://cloud.google.com/bigquery>Google Cloud BigQuery</a>
- *         <li><a href=https://cloud.google.com/bigtable>Cloud BigTable</a>
+ *         <li><a href=https://cloud.google.com/bigtable>Cloud Bigtable</a>
  *       </ul>
  *   <li>A configured tokenization server
  * </ul>
@@ -138,13 +138,13 @@
  *         - <b><i>bigQueryTableName</i></b>: Cloud BigQuery table name to write into
  *         - <b><i>tempLocation</i></b>: Folder in a Google Cloud Storage bucket, which is needed for
  *           BigQuery to handle data writing
- *     - Cloud BigTable
- *         - <b><i>bigTableProjectId</i></b>: Id of the project where the Cloud BigTable instance to write into
+ *     - Cloud Bigtable
+ *         - <b><i>bigTableProjectId</i></b>: Id of the project where the Cloud Bigtable instance to write into
  *           is located
- *         - <b><i>bigTableInstanceId</i></b>: Id of the Cloud BigTable instance to write into
- *         - <b><i>bigTableTableId</i></b>: Id of the Cloud BigTable table to write into
- *         - <b><i>bigTableKeyColumnName</i></b>: Column name to use as a key in Cloud BigTable
- *         - <b><i>bigTableColumnFamilyName</i></b>: Column family name to use in Cloud BigTable
+ *         - <b><i>bigTableInstanceId</i></b>: Id of the Cloud Bigtable instance to write into
+ *         - <b><i>bigTableTableId</i></b>: Id of the Cloud Bigtable table to write into
+ *         - <b><i>bigTableKeyColumnName</i></b>: Column name to use as a key in Cloud Bigtable
+ *         - <b><i>bigTableColumnFamilyName</i></b>: Column family name to use in Cloud Bigtable
  * - RPC server parameters
  *     - <b><i>rpcUri</i></b>: URI for the API calls to RPC server
  *     - <b><i>batchSize</i></b>: Size of the batch to send to RPC server per request
@@ -335,7 +335,7 @@ public static PipelineResult run(DataTokenizationOptions options) {
           .write(tokenizedRows.get(TOKENIZATION_OUT), schema.getBeamSchema());
     } else {
       throw new IllegalStateException(
-          "No sink is provided, please configure BigQuery or BigTable.");
+          "No sink is provided, please configure BigQuery or Bigtable.");
     }
 
     return pipeline.run();

examples/java/src/main/java/org/apache/beam/examples/complete/datatokenization/README.md

@@ -36,7 +36,7 @@ Supported destination sinks:
 
 - File system
 - [Google Cloud BigQuery](https://cloud.google.com/bigquery)
-- [Cloud BigTable](https://cloud.google.com/bigtable)
+- [Cloud Bigtable](https://cloud.google.com/bigtable)
 
 Supported data schema format:
 
@@ -122,13 +122,13 @@ To execute this pipeline, specify the parameters:
         - **bigQueryTableName**: Cloud BigQuery table name to write into
         - **tempLocation**: Folder in a Google Cloud Storage bucket, which is needed for
           BigQuery to handle data writing
-    - Cloud BigTable
-        - **bigTableProjectId**: Id of the project where the Cloud BigTable instance to write into
+    - Cloud Bigtable
+        - **bigTableProjectId**: Id of the project where the Cloud Bigtable instance to write into
           is located
-        - **bigTableInstanceId**: Id of the Cloud BigTable instance to write into
-        - **bigTableTableId**: Id of the Cloud BigTable table to write into
-        - **bigTableKeyColumnName**: Column name to use as a key in Cloud BigTable
-        - **bigTableColumnFamilyName**: Column family name to use in Cloud BigTable
+        - **bigTableInstanceId**: Id of the Cloud Bigtable instance to write into
+        - **bigTableTableId**: Id of the Cloud Bigtable table to write into
+        - **bigTableKeyColumnName**: Column name to use as a key in Cloud Bigtable
+        - **bigTableColumnFamilyName**: Column family name to use in Cloud Bigtable
 - RPC server parameters
     - **rpcUri**: URI for the API calls to RPC server
     - **batchSize**: Size of the batch to send to RPC server per request

examples/java/src/main/java/org/apache/beam/examples/complete/datatokenization/transforms/io/TokenizationBigQueryIO.java

@@ -34,7 +34,7 @@
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
-/** The {@link TokenizationBigQueryIO} class for writing data from template to BigTable. */
+/** The {@link TokenizationBigQueryIO} class for writing data from template to BigQuery. */
 public class TokenizationBigQueryIO {
 
   /** Logger for class. */

examples/java/src/main/java/org/apache/beam/examples/complete/datatokenization/transforms/io/TokenizationBigTableIO.java

@@ -40,7 +40,7 @@
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
-/** The {@link TokenizationBigTableIO} class for writing data from template to BigTable. */
+/** The {@link TokenizationBigTableIO} class for writing data from template to Bigtable. */
 public class TokenizationBigTableIO {
 
   /** Logger for class. */
@@ -101,7 +101,7 @@ public void processElement(
                                   .build())
                           .build())
               .collect(Collectors.toSet());
-      // Converting key value to BigTable format
+      // Converting key value to Bigtable format
       String columnName = in.getString(options.getBigTableKeyColumnName());
       if (columnName != null) {
         ByteString key = ByteString.copyFrom(columnName, StandardCharsets.UTF_8);
@@ -128,31 +128,31 @@ public void processElement(@Element BigtableWriteResult in) {
 
   /**
    * Necessary {@link PipelineOptions} options for Pipelines that perform write operations to
-   * BigTable.
+   * Bigtable.
    */
   public interface BigTableOptions extends PipelineOptions {
 
-    @Description("Id of the project where the Cloud BigTable instance to write into is located.")
+    @Description("Id of the project where the Cloud Bigtable instance to write into is located.")
     String getBigTableProjectId();
 
     void setBigTableProjectId(String bigTableProjectId);
 
-    @Description("Id of the Cloud BigTable instance to write into.")
+    @Description("Id of the Cloud Bigtable instance to write into.")
     String getBigTableInstanceId();
 
     void setBigTableInstanceId(String bigTableInstanceId);
 
-    @Description("Id of the Cloud BigTable table to write into.")
+    @Description("Id of the Cloud Bigtable table to write into.")
     String getBigTableTableId();
 
     void setBigTableTableId(String bigTableTableId);
 
-    @Description("Column name to use as a key in Cloud BigTable.")
+    @Description("Column name to use as a key in Cloud Bigtable.")
     String getBigTableKeyColumnName();
 
     void setBigTableKeyColumnName(String bigTableKeyColumnName);
 
-    @Description("Column family name to use in Cloud BigTable.")
+    @Description("Column family name to use in Cloud Bigtable.")
     String getBigTableColumnFamilyName();
 
     void setBigTableColumnFamilyName(String bigTableColumnFamilyName);

it/google-cloud-platform/src/test/java/org/apache/beam/it/gcp/bigtable/BigTableIOLT.java

@@ -53,7 +53,7 @@
 import org.junit.Test;
 
 /**
- * BigTableIO performance tests.
+ * BigtableIO performance tests.
  *
  * <p>Example trigger command for all tests: "mvn test -pl it/google-cloud-platform -am
  * -Dtest=BigTableIOLT \ -Dproject=[gcpProject] -DartifactBucket=[temp bucket]
@@ -248,7 +248,7 @@ abstract static class Builder {
     abstract Builder toBuilder();
   }
 
-  /** Maps long number to the BigTable format record. */
+  /** Maps long number to the Bigtable format record. */
   private static class MapToBigTableFormat extends DoFn<Long, KV<ByteString, Iterable<Mutation>>>
       implements Serializable {
 

it/google-cloud-platform/src/test/java/org/apache/beam/it/gcp/bigtable/BigTableIOST.java

@@ -62,7 +62,7 @@
 import org.junit.Test;
 
 /**
- * BigTableIO stress test. The test is designed to assess the performance of BigTableIO under
+ * BigtableIO stress test. The test is designed to assess the performance of BigtableIO under
  * various conditions.
  *
  * <p>Usage: <br>
@@ -229,7 +229,7 @@ public void runTest() throws IOException, ParseException, InterruptedException {
   }
 
   /**
-   * The method creates a pipeline to simulate data generation and write operations to BigTable,
+   * The method creates a pipeline to simulate data generation and write operations to Bigtable,
    * based on the specified configuration parameters. The stress test involves varying the load
    * dynamically over time, with options to use configurable parameters.
    */
@@ -278,7 +278,7 @@ private PipelineLauncher.LaunchInfo generateDataAndWrite() throws IOException {
     return pipelineLauncher.launch(project, region, options);
   }
 
-  /** The method reads data from BigTable in batch mode. */
+  /** The method reads data from Bigtable in batch mode. */
   private PipelineLauncher.LaunchInfo readData() throws IOException {
     BigtableIO.Read readIO =
         BigtableIO.read()
@@ -307,7 +307,7 @@ private PipelineLauncher.LaunchInfo readData() throws IOException {
     return pipelineLauncher.launch(project, region, options);
   }
 
-  /** Options for BigTableIO stress test. */
+  /** Options for BigtableIO stress test. */
   static class Configuration extends SyntheticSourceOptions {
     /** Pipeline timeout in minutes. Must be a positive value. */
     @JsonProperty public int pipelineTimeout = 20;
@@ -347,7 +347,7 @@ static class Configuration extends SyntheticSourceOptions {
     @JsonProperty public String influxDatabase;
   }
 
-  /** Maps Instant to the BigTable format record. */
+  /** Maps Instant to the Bigtable format record. */
   private static class MapToBigTableFormat
       extends DoFn<KV<byte[], byte[]>, KV<ByteString, Iterable<Mutation>>> implements Serializable {
 

learning/prompts/code-generation/04_io_bigtable.md

@@ -60,7 +60,7 @@ if __name__ == "__main__":
 ```
 The `ReadFromBigtable` transform returns a `PCollection` of `PartialRowData` objects, each representing a Bigtable row. For more information about this row object, see [PartialRowData (row_key)](https://cloud.google.com/python/docs/reference/bigtable/latest/row#class-googlecloudbigtablerowpartialrowdatarowkey).
 
-For more information, see the [BigTable I/O connector documentation](https://beam.apache.org/releases/pydoc/current/apache_beam.io.gcp.bigtableio.html).
+For more information, see the [Bigtable I/O connector documentation](https://beam.apache.org/releases/pydoc/current/apache_beam.io.gcp.bigtableio.html).
 
 For samples that show common pipeline configurations, see [Pipeline option patterns](https://beam.apache.org/documentation/patterns/pipeline-options/).
 

learning/prompts/code-generation/java/04_io_bigtable.md

@@ -2,9 +2,9 @@ Prompt:
 Write a sample Java code snippet that writes data to a Google Bigtable table using Apache Beam.
 
 Response:
-Your Apache Beam pipeline can write data to a Bigtable table using the Apache Beam BigTableIO connector.
+Your Apache Beam pipeline can write data to a Bigtable table using the Apache Beam BigtableIO connector.
 
-Here is an example of how to use the BigTableIO connector to accomplish this:
+Here is an example of how to use the BigtableIO connector to accomplish this:
 
 ```java
  package bigtable;

sdks/java/core/src/main/java/org/apache/beam/sdk/io/range/RangeTracker.java

@@ -76,7 +76,7 @@
  * after A, up to but not including the first record starting at or after B".
  *
  * <p>Some examples of such sources include reading lines or CSV from a text file, reading keys and
- * values from a BigTable, etc.
+ * values from a Bigtable, etc.
  *
  * <p>The concept of <i>split points</i> allows to extend the definitions for dealing with sources
  * where some records cannot be identified by a unique starting position.

sdks/java/extensions/sql/src/main/java/org/apache/beam/sdk/extensions/sql/meta/provider/bigtable/BigtableTableProvider.java

@@ -27,7 +27,7 @@
 /**
  * {@link TableProvider} for {@link BigtableTable}.
  *
- * <p>A sample of BigTable table is:
+ * <p>A sample of Bigtable table is:
  *
  * <pre>{@code
  *   CREATE EXTERNAL TABLE beamTable(

sdks/java/extensions/sql/src/main/java/org/apache/beam/sdk/extensions/sql/meta/provider/bigtable/package-info.java

@@ -16,5 +16,5 @@
  * limitations under the License.
  */
 
-/** Table schema for BigTable. */
+/** Table schema for Bigtable. */
 package org.apache.beam.sdk.extensions.sql.meta.provider.bigtable;

sdks/java/io/google-cloud-platform/src/main/java/org/apache/beam/sdk/io/gcp/bigquery/StorageApiWriteUnshardedRecords.java

@@ -839,7 +839,7 @@ long flush(
               }
               if (schemaMismatchError) {
                 LOG.info(
-                    "Vortex failed stream open due to incompatible fields. This is likely because the BigTable "
+                    "Vortex failed stream open due to incompatible fields. This is likely because the Bigtable "
                         + "schema was recently updated and Vortex hasn't noticed yet, so retrying. error {}",
                     Preconditions.checkStateNotNull(error).toString());
               }

sdks/java/io/google-cloud-platform/src/main/java/org/apache/beam/sdk/io/gcp/bigtable/BigtableConfig.java

@@ -128,12 +128,12 @@ abstract Builder setBigtableOptionsConfigurator(
   }
 
   public BigtableConfig withProjectId(ValueProvider<String> projectId) {
-    checkArgument(projectId != null, "Project Id of BigTable can not be null");
+    checkArgument(projectId != null, "Project Id of Bigtable can not be null");
     return toBuilder().setProjectId(projectId).build();
   }
 
   public BigtableConfig withInstanceId(ValueProvider<String> instanceId) {
-    checkArgument(instanceId != null, "Instance Id of BigTable can not be null");
+    checkArgument(instanceId != null, "Instance Id of Bigtable can not be null");
     return toBuilder().setInstanceId(instanceId).build();
   }
 

sdks/java/io/google-cloud-platform/src/main/java/org/apache/beam/sdk/io/gcp/bigtable/BigtableIO.java

@@ -112,7 +112,7 @@
 /**
  * {@link PTransform Transforms} for reading from and writing to Google Cloud Bigtable.
  *
- * <p>Please note the Cloud BigTable HBase connector available <a
+ * <p>Please note the Cloud Bigtable HBase connector available <a
  * href="https://github.com/googleapis/java-bigtable-hbase/tree/master/bigtable-dataflow-parent/bigtable-hbase-beam">here</a>.
  * We recommend using that connector over this one if <a
  * href="https://cloud.google.com/bigtable/docs/hbase-bigtable">HBase API</a></> works for your

sdks/java/io/google-cloud-platform/src/test/java/org/apache/beam/sdk/io/gcp/bigtable/BigtableIOTest.java

@@ -1641,7 +1641,7 @@ public void testGetSplitPointsConsumed() throws Exception {
   }
 
   @Test
-  public void testReadWithBigTableOptionsSetsRetryOptions() {
+  public void testReadWithBigtableOptionsSetsRetryOptions() {
     final int initialBackoffMillis = -1;
 
     BigtableOptions.Builder optionsBuilder = BIGTABLE_OPTIONS.toBuilder();
@@ -1660,7 +1660,7 @@ public void testReadWithBigTableOptionsSetsRetryOptions() {
   }
 
   @Test
-  public void testWriteWithBigTableOptionsSetsBulkOptionsAndRetryOptions() {
+  public void testWriteWithBigtableOptionsSetsBulkOptionsAndRetryOptions() {
     final int maxInflightRpcs = 1;
     final int initialBackoffMillis = -1;
 

sdks/python/apache_beam/examples/snippets/transforms/elementwise/enrichment.py

@@ -46,7 +46,7 @@ def enrichment_with_bigtable():
     _ = (
         p
         | "Create" >> beam.Create(data)
-        | "Enrich W/ BigTable" >> Enrichment(bigtable_handler)
+        | "Enrich W/ Bigtable" >> Enrichment(bigtable_handler)
         | "Print" >> beam.Map(print))
   # [END enrichment_with_bigtable]
 

sdks/python/apache_beam/io/gcp/bigtableio.py

@@ -15,18 +15,18 @@
 # limitations under the License.
 #
 
-"""BigTable connector
+"""Bigtable connector
 
-This module implements writing to BigTable tables.
-The default mode is to set row data to write to BigTable tables.
+This module implements writing to Bigtable tables.
+The default mode is to set row data to write to Bigtable tables.
 The syntax supported is described here:
 https://cloud.google.com/bigtable/docs/quickstart-cbt
 
-BigTable connector can be used as main outputs. A main output
+Bigtable connector can be used as main outputs. A main output
 (common case) is expected to be massive and will be split into
 manageable chunks and processed in parallel. In the example below
 we created a list of rows then passed to the GeneratedDirectRows
-DoFn to set the Cells and then we call the BigTableWriteFn to insert
+DoFn to set the Cells and then we call the _BigTableWriteFn to insert
 those generated rows in the table.
 
   main_table = (p

sdks/python/apache_beam/io/gcp/bigtableio_it_test.py

@@ -15,7 +15,7 @@
 # limitations under the License.
 #
 
-"""Integration tests for BigTable service."""
+"""Integration tests for Bigtable service."""
 
 import logging
 import os
@@ -66,7 +66,7 @@ def instance_prefix(instance):
     os.environ.get('TRANSFORM_SERVICE_PORT'),
     "A valid expansion service is not available for executing the "
     "cross-language test.")
-class TestReadFromBigTableIT(unittest.TestCase):
+class TestReadFromBigtableIT(unittest.TestCase):
   INSTANCE = "bt-read-tests"
   TABLE_ID = "test-table"
 

sdks/python/apache_beam/io/gcp/bigtableio_test.py

@@ -15,7 +15,7 @@
 # limitations under the License.
 #
 
-"""Unit tests for BigTable service."""
+"""Unit tests for Bigtable service."""
 
 import logging
 import string

sdks/python/apache_beam/io/iobase.py

@@ -295,7 +295,7 @@ class RangeTracker(object):
   at or after 'B'".
 
   Some examples of such sources include reading lines or CSV from a text file,
-  reading keys and values from a BigTable, etc.
+  reading keys and values from a Bigtable, etc.
 
   The concept of *split points* allows to extend the definitions for dealing
   with sources where some records cannot be identified by a unique starting

sdks/python/apache_beam/testing/analyzers/io_tests_config.yaml

@@ -185,7 +185,7 @@ bigquery_io_json_file_loads_write:
 
 bigtable_io_read:
   test_description: |
-    BigTableIO read test 100 GB.
+    BigtableIO read test 100 GB.
   project: apache-beam-testing
   metrics_dataset: performance_tests
   metrics_table: io_performance_metrics
@@ -197,7 +197,7 @@ bigtable_io_read:
 
 bigtable_io_write:
   test_description: |
-    BigTableIO write test 100 GB.
+    BigtableIO write test 100 GB.
   project: apache-beam-testing
   metrics_dataset: performance_tests
   metrics_table: io_performance_metrics