Use apache-beam-testing.samples (#28064)

* Use apache-beam-testing.samples * run ./gradlew :examples:java:spotlessApply
apache · Aug 20, 2023 · 44aea4b · 44aea4b
1 parent 26b7772
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diff --git a/examples/java/src/main/java/org/apache/beam/examples/cookbook/BigQueryTornadoes.java b/examples/java/src/main/java/org/apache/beam/examples/cookbook/BigQueryTornadoes.java
@@ -63,15 +63,15 @@
  *
  * See examples/java/README.md for instructions about how to configure different runners.
  *
- * <p>The BigQuery input table defaults to {@code clouddataflow-readonly:samples.weather_stations}
- * and can be overridden with {@code --input}.
+ * <p>The BigQuery input table defaults to {@code apache-beam-testing.samples.weather_stations} and
+ * can be overridden with {@code --input}.
  */
 public class BigQueryTornadoes {
   private static final Logger LOG = LoggerFactory.getLogger(BigQueryTornadoes.class);
 
   // Default to using a 1000 row subset of the public weather station table publicdata:samples.gsod.
   private static final String WEATHER_SAMPLES_TABLE =
-      "clouddataflow-readonly:samples.weather_stations";
+      "apache-beam-testing.samples.weather_stations";
 
   /**
    * Examines each row in the input table. If a tornado was recorded in that sample, the month in

diff --git a/examples/java/src/main/java/org/apache/beam/examples/cookbook/FilterExamples.java b/examples/java/src/main/java/org/apache/beam/examples/cookbook/FilterExamples.java
@@ -71,13 +71,13 @@
  *
  * See examples/java/README.md for instructions about how to configure different runners.
  *
- * <p>The BigQuery input table defaults to {@code clouddataflow-readonly:samples.weather_stations}
- * and can be overridden with {@code --input}.
+ * <p>The BigQuery input table defaults to {@code apache-beam-testing.samples.weather_stations} and
+ * can be overridden with {@code --input}.
  */
 public class FilterExamples {
   // Default to using a 1000 row subset of the public weather station table publicdata:samples.gsod.
   private static final String WEATHER_SAMPLES_TABLE =
-      "clouddataflow-readonly:samples.weather_stations";
+      "apache-beam-testing.samples.weather_stations";
   static final Logger LOG = Logger.getLogger(FilterExamples.class.getName());
   static final int MONTH_TO_FILTER = 7;
 

diff --git a/examples/java/src/main/java/org/apache/beam/examples/cookbook/JoinExamples.java b/examples/java/src/main/java/org/apache/beam/examples/cookbook/JoinExamples.java
@@ -58,7 +58,7 @@
 public class JoinExamples {
 
   // A 1000-row sample of the GDELT data here: gdelt-bq:full.events.
-  private static final String GDELT_EVENTS_TABLE = "clouddataflow-readonly:samples.gdelt_sample";
+  private static final String GDELT_EVENTS_TABLE = "apache-beam-testing.samples.gdelt_sample";
   // A table that maps country codes to country names.
   private static final String COUNTRY_CODES = "gdelt-bq:full.crosswalk_geocountrycodetohuman";
 

diff --git a/examples/java/src/main/java/org/apache/beam/examples/cookbook/MaxPerKeyExamples.java b/examples/java/src/main/java/org/apache/beam/examples/cookbook/MaxPerKeyExamples.java
@@ -59,13 +59,13 @@
  *
  * See examples/java/README.md for instructions about how to configure different runners.
  *
- * <p>The BigQuery input table defaults to {@code clouddataflow-readonly:samples.weather_stations }
- * and can be overridden with {@code --input}.
+ * <p>The BigQuery input table defaults to {@code apache-beam-testing.samples.weather_stations } and
+ * can be overridden with {@code --input}.
  */
 public class MaxPerKeyExamples {
   // Default to using a 1000 row subset of the public weather station table publicdata:samples.gsod.
   private static final String WEATHER_SAMPLES_TABLE =
-      "clouddataflow-readonly:samples.weather_stations";
+      "apache-beam-testing.samples.weather_stations";
 
   /**
    * Examines each row (weather reading) in the input table. Output the month of the reading, and

diff --git a/examples/java/src/main/java/org/apache/beam/examples/cookbook/MinimalBigQueryTornadoes.java b/examples/java/src/main/java/org/apache/beam/examples/cookbook/MinimalBigQueryTornadoes.java
@@ -58,14 +58,14 @@
  *
  * <p>Concepts: Reading/writing BigQuery; counting a PCollection; user-defined PTransforms
  *
- * <p>The BigQuery input is taken from {@code clouddataflow-readonly:samples.weather_stations}
+ * <p>The BigQuery input is taken from {@code apache-beam-testing.samples.weather_stations}
  */
 public class MinimalBigQueryTornadoes {
   private static final Logger LOG = LoggerFactory.getLogger(MinimalBigQueryTornadoes.class);
 
   // Use a 1000 row subset of the public weather station table publicdata:samples.gsod.
   private static final String WEATHER_SAMPLES_TABLE =
-      "clouddataflow-readonly:samples.weather_stations";
+      "apache-beam-testing.samples.weather_stations";
 
   /**
    * Examines each row in the input table. If a tornado was recorded in that sample, the month in

diff --git a/examples/java/src/main/java/org/apache/beam/examples/snippets/Snippets.java b/examples/java/src/main/java/org/apache/beam/examples/snippets/Snippets.java
@@ -172,7 +172,7 @@ public static void modelBigQueryIO(
       Pipeline p, String writeProject, String writeDataset, String writeTable) {
     {
       // [START BigQueryTableSpec]
-      String tableSpec = "clouddataflow-readonly:samples.weather_stations";
+      String tableSpec = "apache-beam-testing.samples.weather_stations";
       // [END BigQueryTableSpec]
     }
 
@@ -212,7 +212,7 @@ public static void modelBigQueryIO(
     }
 
     {
-      String tableSpec = "clouddataflow-readonly:samples.weather_stations";
+      String tableSpec = "apache-beam-testing.samples.weather_stations";
       // [START BigQueryReadTable]
       PCollection<Double> maxTemperatures =
           p.apply(BigQueryIO.readTableRows().from(tableSpec))
@@ -224,7 +224,7 @@ public static void modelBigQueryIO(
     }
 
     {
-      String tableSpec = "clouddataflow-readonly:samples.weather_stations";
+      String tableSpec = "apache-beam-testing.samples.weather_stations";
       // [START BigQueryReadFunction]
       PCollection<Double> maxTemperatures =
           p.apply(
@@ -242,7 +242,7 @@ public static void modelBigQueryIO(
               BigQueryIO.read(
                       (SchemaAndRecord elem) -> (Double) elem.getRecord().get("max_temperature"))
                   .fromQuery(
-                      "SELECT max_temperature FROM [clouddataflow-readonly:samples.weather_stations]")
+                      "SELECT max_temperature FROM [apache-beam-testing.samples.weather_stations]")
                   .withCoder(DoubleCoder.of()));
       // [END BigQueryReadQuery]
     }
@@ -280,7 +280,7 @@ public static void modelBigQueryIO(
     // [END BigQuerySchemaJson]
 
     {
-      String tableSpec = "clouddataflow-readonly:samples.weather_stations";
+      String tableSpec = "apache-beam-testing.samples.weather_stations";
       if (!writeProject.isEmpty() && !writeDataset.isEmpty() && !writeTable.isEmpty()) {
         tableSpec = writeProject + ":" + writeDataset + "." + writeTable;
       }
@@ -403,7 +403,7 @@ public WeatherData(long year, long month, long day, double maxTemp) {
                       })
                   .fromQuery(
                       "SELECT year, month, day, max_temperature "
-                          + "FROM [clouddataflow-readonly:samples.weather_stations] "
+                          + "FROM [apache-beam-testing.samples.weather_stations] "
                           + "WHERE year BETWEEN 2007 AND 2009")
                   .withCoder(AvroCoder.of(WeatherData.class)));
 
@@ -461,7 +461,7 @@ public TableSchema getSchema(Long destination) {
               .withWriteDisposition(WriteDisposition.WRITE_TRUNCATE));
       // [END BigQueryWriteDynamicDestinations]
 
-      String tableSpec = "clouddataflow-readonly:samples.weather_stations";
+      String tableSpec = "apache-beam-testing.samples.weather_stations";
       if (!writeProject.isEmpty() && !writeDataset.isEmpty() && !writeTable.isEmpty()) {
         tableSpec = writeProject + ":" + writeDataset + "." + writeTable + "_partitioning";
       }

diff --git a/examples/kotlin/src/main/java/org/apache/beam/examples/kotlin/cookbook/BigQueryTornadoes.kt b/examples/kotlin/src/main/java/org/apache/beam/examples/kotlin/cookbook/BigQueryTornadoes.kt
@@ -60,12 +60,12 @@ import org.apache.beam.vendor.guava.v32_1_2_jre.com.google.common.collect.Lists
  * See examples/java/README.md for instructions about how to configure different runners.
  *
  *
- * The BigQuery input table defaults to `clouddataflow-readonly:samples.weather_stations`
+ * The BigQuery input table defaults to `apache-beam-testing.samples.weather_stations`
  * and can be overridden with `--input`.
  */
 object BigQueryTornadoes {
     // Default to using a 1000 row subset of the public weather station table publicdata:samples.gsod.
-    private const val WEATHER_SAMPLES_TABLE = "clouddataflow-readonly:samples.weather_stations"
+    private const val WEATHER_SAMPLES_TABLE = "apache-beam-testing.samples.weather_stations"
 
     /**
      * Examines each row in the input table. If a tornado was recorded in that sample, the month in

diff --git a/examples/kotlin/src/main/java/org/apache/beam/examples/kotlin/cookbook/FilterExamples.kt b/examples/kotlin/src/main/java/org/apache/beam/examples/kotlin/cookbook/FilterExamples.kt
@@ -65,12 +65,12 @@ import java.util.logging.Logger
  * See examples/kotlin/README.md for instructions about how to configure different runners.
  *
  *
- * The BigQuery input table defaults to `clouddataflow-readonly:samples.weather_stations`
+ * The BigQuery input table defaults to `apache-beam-testing.samples.weather_stations`
  * and can be overridden with `--input`.
  */
 object FilterExamples {
     // Default to using a 1000 row subset of the public weather station table publicdata:samples.gsod.
-    private const val WEATHER_SAMPLES_TABLE = "clouddataflow-readonly:samples.weather_stations"
+    private const val WEATHER_SAMPLES_TABLE = "apache-beam-testing.samples.weather_stations"
     internal val LOG = Logger.getLogger(FilterExamples::class.java.name)
     internal const val MONTH_TO_FILTER = 7
 

diff --git a/examples/kotlin/src/main/java/org/apache/beam/examples/kotlin/cookbook/JoinExamples.kt b/examples/kotlin/src/main/java/org/apache/beam/examples/kotlin/cookbook/JoinExamples.kt
@@ -60,7 +60,7 @@ import org.apache.beam.sdk.values.TupleTag
 object JoinExamples {
 
     // A 1000-row sample of the GDELT data here: gdelt-bq:full.events.
-    private const val GDELT_EVENTS_TABLE = "clouddataflow-readonly:samples.gdelt_sample"
+    private const val GDELT_EVENTS_TABLE = "apache-beam-testing.samples.gdelt_sample"
     // A table that maps country codes to country names.
     private const val COUNTRY_CODES = "gdelt-bq:full.crosswalk_geocountrycodetohuman"
 

diff --git a/examples/kotlin/src/main/java/org/apache/beam/examples/kotlin/cookbook/MaxPerKeyExamples.kt b/examples/kotlin/src/main/java/org/apache/beam/examples/kotlin/cookbook/MaxPerKeyExamples.kt
@@ -60,12 +60,12 @@ import java.util.ArrayList
  * See examples/java/README.md for instructions about how to configure different runners.
  *
  *
- * The BigQuery input table defaults to `clouddataflow-readonly:samples.weather_stations `
+ * The BigQuery input table defaults to `apache-beam-testing.samples.weather_stations `
  * and can be overridden with `--input`.
  */
 object MaxPerKeyExamples {
     // Default to using a 1000 row subset of the public weather station table publicdata:samples.gsod.
-    private const val WEATHER_SAMPLES_TABLE = "clouddataflow-readonly:samples.weather_stations"
+    private const val WEATHER_SAMPLES_TABLE = "apache-beam-testing.samples.weather_stations"
 
     /**
      * Examines each row (weather reading) in the input table. Output the month of the reading, and

diff --git a/examples/kotlin/src/main/java/org/apache/beam/examples/kotlin/snippets/Snippets.kt b/examples/kotlin/src/main/java/org/apache/beam/examples/kotlin/snippets/Snippets.kt
@@ -84,7 +84,7 @@ object Snippets {
             pipeline: Pipeline, writeProject: String = "", writeDataset: String = "", writeTable: String = "") {
         run {
             // [START BigQueryTableSpec]
-            val tableSpec = "clouddataflow-readonly:samples.weather_stations"
+            val tableSpec = "apache-beam-testing.samples.weather_stations"
             // [END BigQueryTableSpec]
         }
 
@@ -104,7 +104,7 @@ object Snippets {
         }
 
         run {
-            val tableSpec = "clouddataflow-readonly:samples.weather_stations"
+            val tableSpec = "apache-beam-testing.samples.weather_stations"
             // [START BigQueryReadTable]
             val maxTemperatures = pipeline.apply(BigQueryIO.readTableRows().from(tableSpec))
                     // Each row is of type TableRow
@@ -118,7 +118,7 @@ object Snippets {
         }
 
         run {
-            val tableSpec = "clouddataflow-readonly:samples.weather_stations"
+            val tableSpec = "apache-beam-testing.samples.weather_stations"
             // [START BigQueryReadFunction]
             val maxTemperatures = pipeline.apply(
                     BigQueryIO.read { it.record["max_temperature"] as Double? }
@@ -132,7 +132,7 @@ object Snippets {
             val maxTemperatures = pipeline.apply(
                     BigQueryIO.read { it.record["max_temperature"] as Double? }
                             .fromQuery(
-                                    "SELECT max_temperature FROM [clouddataflow-readonly:samples.weather_stations]")
+                                    "SELECT max_temperature FROM [apache-beam-testing.samples.weather_stations]")
                             .withCoder(DoubleCoder.of()))
             // [END BigQueryReadQuery]
         }
@@ -167,7 +167,7 @@ object Snippets {
         // [END BigQuerySchemaJson]
 
         run {
-            var tableSpec = "clouddataflow-readonly:samples.weather_stations"
+            var tableSpec = "apache-beam-testing.samples.weather_stations"
             if (writeProject.isNotEmpty() && writeDataset.isNotEmpty() && writeTable.isNotEmpty()) {
                 tableSpec = "$writeProject:$writeDataset.$writeTable"
             }
@@ -259,7 +259,7 @@ object Snippets {
                     }
                             .fromQuery("""
                                 SELECT year, month, day, max_temperature
-                                FROM [clouddataflow-readonly:samples.weather_stations]
+                                FROM [apache-beam-testing.samples.weather_stations]
                                 WHERE year BETWEEN 2007 AND 2009
                             """.trimIndent())
                             .withCoder(AvroCoder.of(WeatherData::class.java)))
@@ -297,7 +297,7 @@ object Snippets {
                             .withWriteDisposition(WriteDisposition.WRITE_TRUNCATE))
             // [END BigQueryWriteDynamicDestinations]
 
-            var tableSpec = "clouddataflow-readonly:samples.weather_stations"
+            var tableSpec = "apache-beam-testing.samples.weather_stations"
             if (writeProject.isNotEmpty() && writeDataset.isNotEmpty() && writeTable.isNotEmpty()) {
                 tableSpec = "$writeProject:$writeDataset.${writeTable}_partitioning"
             }

diff --git a/learning/tour-of-beam/learning-content/io/big-query-io/read-table/description.md b/learning/tour-of-beam/learning-content/io/big-query-io/read-table/description.md
@@ -35,7 +35,7 @@ The `logOutput` struct is defined as a custom `DoFn` that implements the Process
 {{if (eq .Sdk "java")}}
 ```
  PCollection<TableRow> pCollection = pipeline
-                .apply("ReadFromBigQuery", BigQueryIO.readTableRows().from("clouddataflow-readonly:samples.weather_stations").withMethod(TypedRead.Method.DIRECT_READ))
+                .apply("ReadFromBigQuery", BigQueryIO.readTableRows().from("apache-beam-testing.samples.weather_stations").withMethod(TypedRead.Method.DIRECT_READ))
 ```
 
 The `BigQueryIO.readTableRows()` method is called to create a `BigQueryIO.Read` transform that will read data from a `BigQuery` table.

diff --git a/learning/tour-of-beam/learning-content/io/big-query-io/read-table/java-example/Task.java b/learning/tour-of-beam/learning-content/io/big-query-io/read-table/java-example/Task.java
@@ -65,7 +65,7 @@ public static void main(String[] args) {
          */
 
         PCollection<TableRow> pCollection = pipeline
-                .apply("ReadFromBigQuery", BigQueryIO.readTableRows().from("clouddataflow-readonly:samples.weather_stations").withMethod(TypedRead.Method.DIRECT_READ));
+                .apply("ReadFromBigQuery", BigQueryIO.readTableRows().from("apache-beam-testing.samples.weather_stations").withMethod(TypedRead.Method.DIRECT_READ));
 
         final PTransform<PCollection<TableRow>, PCollection<Iterable<TableRow>>> sample = Sample.fixedSizeGlobally(5);
 

diff --git a/learning/tour-of-beam/learning-content/io/rest-api/description.md b/learning/tour-of-beam/learning-content/io/rest-api/description.md
@@ -31,7 +31,7 @@ PCollection<WeatherData> weatherData =
                 })
             .fromQuery(
                 "SELECT year, month, day, max_temperature "
-                    + "FROM [clouddataflow-readonly:samples.weather_stations] "
+                    + "FROM [apache-beam-testing.samples.weather_stations] "
                     + "WHERE year BETWEEN 2007 AND 2009")
             .withCoder(AvroCoder.of(WeatherData.class)));
 

diff --git a/playground/backend/internal/fs_tool/ExampleData.scala b/playground/backend/internal/fs_tool/ExampleData.scala
@@ -26,8 +26,8 @@ object ExampleData {
     "gs://apache-beam-samples/traffic_sensor/Freeways-5Minaa2010-01-01_to_2010-02-15_test2.csv"
   val GAMING = "gs://apache-beam-samples/game/gaming_data*.csv"
 
-  val WEATHER_SAMPLES_TABLE = "clouddataflow-readonly:samples.weather_stations"
+  val WEATHER_SAMPLES_TABLE = "apache-beam-testing.samples.weather_stations"
   val SHAKESPEARE_TABLE = "bigquery-public-data:samples.shakespeare"
-  val EVENT_TABLE = "clouddataflow-readonly:samples.gdelt_sample"
+  val EVENT_TABLE = "apache-beam-testing.samples.gdelt_sample"
   val COUNTRY_TABLE = "gdelt-bq:full.crosswalk_geocountrycodetohuman"
 }
diff --git a/sdks/go/examples/cookbook/filter/filter.go b/sdks/go/examples/cookbook/filter/filter.go
@@ -32,7 +32,7 @@ import (
 )
 
 var (
-	input  = flag.String("input", "clouddataflow-readonly:samples.weather_stations", "Weather data BQ table.")
+	input  = flag.String("input", "apache-beam-testing.samples.weather_stations", "Weather data BQ table.")
 	output = flag.String("output", "", "Output BQ table.")
 	month  = flag.Int("month_filter", 7, "Numerical month to analyze")
 )

diff --git a/sdks/go/examples/cookbook/join/join.go b/sdks/go/examples/cookbook/join/join.go
@@ -34,7 +34,7 @@ import (
 // See: https://github.com/apache/beam/blob/master/examples/java/src/main/java/org/apache/beam/examples/cookbook/JoinExamples.java
 
 const (
-	gdeltEventsTable  = "clouddataflow-readonly:samples.gdelt_sample"
+	gdeltEventsTable  = "apache-beam-testing.samples.gdelt_sample"
 	countryCodesTable = "gdelt-bq:full.crosswalk_geocountrycodetohuman"
 )
 

diff --git a/sdks/go/examples/cookbook/max/max.go b/sdks/go/examples/cookbook/max/max.go
@@ -32,7 +32,7 @@ import (
 )
 
 var (
-	input  = flag.String("input", "clouddataflow-readonly:samples.weather_stations", "Weather data BQ table.")
+	input  = flag.String("input", "apache-beam-testing.samples.weather_stations", "Weather data BQ table.")
 	output = flag.String("output", "", "Output BQ table.")
 )
 

diff --git a/sdks/go/examples/cookbook/tornadoes/tornadoes.go b/sdks/go/examples/cookbook/tornadoes/tornadoes.go
@@ -29,7 +29,7 @@
 //
 //	--output=YOUR_PROJECT_ID:DATASET_ID.TABLE_ID
 //
-// The BigQuery input table defaults to clouddataflow-readonly:samples.weather_stations
+// The BigQuery input table defaults to apache-beam-testing.samples.weather_stations
 // and can be overridden with {@code --input}.
 package main
 
@@ -48,7 +48,7 @@ import (
 )
 
 var (
-	input  = flag.String("input", "clouddataflow-readonly:samples.weather_stations", "BigQuery table with weather data to read from, specified as <project_id>:<dataset_id>.<table_id>")
+	input  = flag.String("input", "apache-beam-testing.samples.weather_stations", "BigQuery table with weather data to read from, specified as <project_id>:<dataset_id>.<table_id>")
 	output = flag.String("output", "", "BigQuery table to write to, specified as <project_id>:<dataset_id>.<table_id>. The dataset must already exist")
 )
 

diff --git a/sdks/java/core/src/main/java/org/apache/beam/sdk/io/package-info.java b/sdks/java/core/src/main/java/org/apache/beam/sdk/io/package-info.java
@@ -24,7 +24,7 @@
  *
  * <pre>{@code
  * PCollection<TableRow> inputData = pipeline.apply(
- *     BigQueryIO.readTableRows().from("clouddataflow-readonly:samples.weather_stations"));
+ *     BigQueryIO.readTableRows().from("apache-beam-testing.samples.weather_stations"));
  * }</pre>
  *
  * and {@code Write} transforms that persist PCollections to external storage:

diff --git a/...o/google-cloud-platform/src/main/java/org/apache/beam/sdk/io/gcp/bigquery/BigQueryIO.java b/...o/google-cloud-platform/src/main/java/org/apache/beam/sdk/io/gcp/bigquery/BigQueryIO.java
@@ -268,7 +268,7 @@
  *
  * <pre>{@code
  * PCollection<TableRow> weatherData = pipeline.apply(
- *     BigQueryIO.readTableRows().from("clouddataflow-readonly:samples.weather_stations"));
+ *     BigQueryIO.readTableRows().from("apache-beam-testing.samples.weather_stations"));
  * }</pre>
  *
  * <b>Example: Reading rows of a table and parsing them into a custom type.</b>
@@ -281,7 +281,7 @@
  *          return new WeatherRecord(...);
  *        }
  *      })
- *      .from("clouddataflow-readonly:samples.weather_stations"))
+ *      .from("apache-beam-testing.samples.weather_stations"))
  *      .withCoder(SerializableCoder.of(WeatherRecord.class));
  * }</pre>
  *

diff --git a/...loud-platform/src/test/java/org/apache/beam/sdk/io/gcp/bigquery/BigQueryClusteringIT.java b/...loud-platform/src/test/java/org/apache/beam/sdk/io/gcp/bigquery/BigQueryClusteringIT.java
@@ -50,7 +50,7 @@ public class BigQueryClusteringIT {
   private static final Long EXPECTED_BYTES = 16000L;
   private static final BigInteger EXPECTED_ROWS = new BigInteger("1000");
   private static final String WEATHER_SAMPLES_TABLE =
-      "clouddataflow-readonly:samples.weather_stations";
+      "apache-beam-testing.samples.weather_stations";
   private static final String DATASET_NAME = "BigQueryClusteringIT";
   private static final Clustering CLUSTERING =
       new Clustering().setFields(Arrays.asList("station_number"));

diff --git a/...c/test/java/org/apache/beam/sdk/io/gcp/bigquery/BigQueryTimePartitioningClusteringIT.java b/...c/test/java/org/apache/beam/sdk/io/gcp/bigquery/BigQueryTimePartitioningClusteringIT.java
@@ -48,7 +48,7 @@
 @RunWith(JUnit4.class)
 public class BigQueryTimePartitioningClusteringIT {
   private static final String WEATHER_SAMPLES_TABLE =
-      "clouddataflow-readonly:samples.weather_stations";
+      "apache-beam-testing.samples.weather_stations";
   private static final String DATASET_NAME = "BigQueryTimePartitioningIT";
   private static final TimePartitioning TIME_PARTITIONING =
       new TimePartitioning().setField("date").setType("DAY");

diff --git a/sdks/python/apache_beam/examples/cookbook/bigquery_tornadoes.py b/sdks/python/apache_beam/examples/cookbook/bigquery_tornadoes.py
@@ -68,7 +68,7 @@ def run(argv=None):
   parser = argparse.ArgumentParser()
   parser.add_argument(
       '--input',
-      default='clouddataflow-readonly:samples.weather_stations',
+      default='apache-beam-testing.samples.weather_stations',
       help=(
           'Input BigQuery table to process specified as: '
           'PROJECT:DATASET.TABLE or DATASET.TABLE.'))