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https://issues.apache.org/jira/browse/BEAM-5191?focusedWorklogId=270476&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-270476
]
ASF GitHub Bot logged work on BEAM-5191:
----------------------------------------
Author: ASF GitHub Bot
Created on: 01/Jul/19 21:13
Start Date: 01/Jul/19 21:13
Worklog Time Spent: 10m
Work Description: jklukas commented on pull request #8945: [BEAM-5191]
Support for BigQuery clustering
URL: https://github.com/apache/beam/pull/8945#discussion_r299220024
##########
File path:
sdks/java/io/google-cloud-platform/src/test/java/org/apache/beam/sdk/io/gcp/bigquery/BigQueryTimePartitioningClusteringIT.java
##########
@@ -0,0 +1,150 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.beam.sdk.io.gcp.bigquery;
+
+import com.google.api.services.bigquery.Bigquery;
+import com.google.api.services.bigquery.model.Clustering;
+import com.google.api.services.bigquery.model.Table;
+import com.google.api.services.bigquery.model.TableFieldSchema;
+import com.google.api.services.bigquery.model.TableRow;
+import com.google.api.services.bigquery.model.TableSchema;
+import com.google.api.services.bigquery.model.TimePartitioning;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.List;
+import org.apache.beam.sdk.Pipeline;
+import org.apache.beam.sdk.io.gcp.testing.BigqueryClient;
+import org.apache.beam.sdk.options.Default;
+import org.apache.beam.sdk.options.Description;
+import org.apache.beam.sdk.options.ExperimentalOptions;
+import org.apache.beam.sdk.options.PipelineOptionsFactory;
+import org.apache.beam.sdk.testing.TestPipeline;
+import org.apache.beam.sdk.testing.TestPipelineOptions;
+import org.apache.beam.sdk.transforms.DoFn;
+import org.apache.beam.sdk.transforms.ParDo;
+import org.junit.Assert;
+import org.junit.Before;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.junit.runners.JUnit4;
+
+/** Integration test that partitions and clusters sample data in BigQuery. */
+@RunWith(JUnit4.class)
+public class BigQueryTimePartitioningClusteringIT {
+ private static final String WEATHER_SAMPLES_TABLE =
+ "clouddataflow-readonly:samples.weather_stations";
+
+ private Bigquery bqClient;
+ private String datasetName = "BigQueryTimePartitioningIT";
+ private BigQueryClusteringITOptions options;
+
+ @Before
+ public void setUp() {
+ PipelineOptionsFactory.register(BigQueryClusteringITOptions.class);
+ options =
TestPipeline.testingPipelineOptions().as(BigQueryClusteringITOptions.class);
+ options.setTempLocation(options.getTempRoot() + "/temp-it/");
+ bqClient = BigqueryClient.getNewBigquerryClient(options.getAppName());
+ }
+
+ /** Customized PipelineOptions for BigQueryClustering Integration Test. */
+ public interface BigQueryClusteringITOptions
+ extends TestPipelineOptions, ExperimentalOptions, BigQueryOptions {
+ @Description("Table to read from, specified as " +
"<project_id>:<dataset_id>.<table_id>")
+ @Default.String(WEATHER_SAMPLES_TABLE)
+ String getInput();
+
+ void setInput(String value);
+ }
+
+ static class KeepStationNumberAndConvertDate extends DoFn<TableRow,
TableRow> {
+ @ProcessElement
+ public void processElement(ProcessContext c) {
+ String day = (String) c.element().get("day");
+ String month = (String) c.element().get("month");
+ String year = (String) c.element().get("year");
+
+ TableRow row = new TableRow();
+ row.set("station_number", c.element().get("station_number"));
+ row.set("date", String.format("%s-%s-%s", year, month, day));
+ c.output(row);
+ }
+ }
+
+ @Test
+ public void testE2EBigQueryTimePartitioning() throws Exception {
+ String tableName = "weather_stations_time_partitioned_" +
System.currentTimeMillis();
+
+ Pipeline p = Pipeline.create(options);
+
+ p.apply(BigQueryIO.readTableRows().from(options.getInput()))
+ .apply(ParDo.of(new KeepStationNumberAndConvertDate()))
+ .apply(
+ BigQueryIO.writeTableRows()
+ .to(String.format("%s.%s", datasetName, tableName))
+ .withTimePartitioning(getTimepartitioning())
+ .withSchema(getSchema())
+
.withCreateDisposition(BigQueryIO.Write.CreateDisposition.CREATE_IF_NEEDED)
+
.withWriteDisposition(BigQueryIO.Write.WriteDisposition.WRITE_TRUNCATE));
+
+ p.run().waitUntilFinish();
Review comment:
I believe these ITs are the work of @wscheep in the previous PR, and I am
going to borrow liberally from these examples to add the dynamic destinations
ITs.
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Issue Time Tracking
-------------------
Worklog Id: (was: 270476)
Time Spent: 9.5h (was: 9h 20m)
> Add support for writing to BigQuery clustered tables
> ----------------------------------------------------
>
> Key: BEAM-5191
> URL: https://issues.apache.org/jira/browse/BEAM-5191
> Project: Beam
> Issue Type: Improvement
> Components: io-java-gcp
> Affects Versions: 2.6.0
> Reporter: Robert Sahlin
> Assignee: Wout Scheepers
> Priority: Minor
> Labels: features, newbie
> Time Spent: 9.5h
> Remaining Estimate: 0h
>
> Google recently added support for clustered tables in BigQuery. It would be
> useful to set clustering columns the same way as for partitioning. It should
> support multiple fields (4) for clustering.
> For example:
> [BigQueryIO.Write|https://beam.apache.org/documentation/sdks/javadoc/2.6.0/org/apache/beam/sdk/io/gcp/bigquery/BigQueryIO.Write.html]<[T|https://beam.apache.org/documentation/sdks/javadoc/2.6.0/org/apache/beam/sdk/io/gcp/bigquery/BigQueryIO.Write.html]>
> .withClustering(new Clustering().setField("productId").setType("STRING"))
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