[HUDI-1764] Add Hudi-CLI support for clustering (#2773)

* tmp base

* update

* update unit test

* update

* update

* update CLI parameters

* linting

* update doSchedule in HoodieClusteringJob

* update

* update diff according to comments

hudi-cli/src/main/java/org/apache/hudi/cli/commands/ClusteringCommand.java

@@ -0,0 +1,107 @@
+/*
+ * 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.hudi.cli.commands;
+
+import org.apache.hudi.cli.HoodieCLI;
+import org.apache.hudi.cli.commands.SparkMain.SparkCommand;
+import org.apache.hudi.cli.utils.InputStreamConsumer;
+import org.apache.hudi.cli.utils.SparkUtil;
+import org.apache.hudi.common.table.HoodieTableMetaClient;
+import org.apache.hudi.common.table.timeline.HoodieActiveTimeline;
+import org.apache.hudi.utilities.UtilHelpers;
+import org.apache.log4j.LogManager;
+import org.apache.log4j.Logger;
+import org.apache.spark.launcher.SparkLauncher;
+import org.apache.spark.util.Utils;
+import org.springframework.shell.core.CommandMarker;
+import org.springframework.shell.core.annotation.CliCommand;
+import org.springframework.shell.core.annotation.CliOption;
+import org.springframework.stereotype.Component;
+import scala.collection.JavaConverters;
+
+@Component
+public class ClusteringCommand implements CommandMarker {
+
+  private static final Logger LOG = LogManager.getLogger(ClusteringCommand.class);
+
+  @CliCommand(value = "clustering schedule", help = "Schedule Clustering")
+  public String scheduleClustering(
+      @CliOption(key = "sparkMemory", help = "Spark executor memory",
+          unspecifiedDefaultValue = "1G") final String sparkMemory,
+      @CliOption(key = "propsFilePath", help = "path to properties file on localfs or dfs with configurations for hoodie client for clustering",
+          unspecifiedDefaultValue = "") final String propsFilePath,
+      @CliOption(key = "hoodieConfigs", help = "Any configuration that can be set in the properties file can be passed here in the form of an array",
+          unspecifiedDefaultValue = "") final String[] configs) throws Exception {
+    HoodieTableMetaClient client = HoodieCLI.getTableMetaClient();
+    boolean initialized = HoodieCLI.initConf();
+    HoodieCLI.initFS(initialized);
+
+    String sparkPropertiesPath =
+        Utils.getDefaultPropertiesFile(JavaConverters.mapAsScalaMapConverter(System.getenv()).asScala());
+    SparkLauncher sparkLauncher = SparkUtil.initLauncher(sparkPropertiesPath);
+
+    // First get a clustering instant time and pass it to spark launcher for scheduling clustering
+    String clusteringInstantTime = HoodieActiveTimeline.createNewInstantTime();
+
+    sparkLauncher.addAppArgs(SparkCommand.CLUSTERING_SCHEDULE.toString(), client.getBasePath(),
+        client.getTableConfig().getTableName(), clusteringInstantTime, sparkMemory, propsFilePath);
+    UtilHelpers.validateAndAddProperties(configs, sparkLauncher);
+    Process process = sparkLauncher.launch();
+    InputStreamConsumer.captureOutput(process);
+    int exitCode = process.waitFor();
+    if (exitCode != 0) {
+      return "Failed to schedule clustering for " + clusteringInstantTime;
+    }
+    return "Succeeded to schedule clustering for " + clusteringInstantTime;
+  }
+
+  @CliCommand(value = "clustering run", help = "Run Clustering")
+  public String runClustering(
+      @CliOption(key = "parallelism", help = "Parallelism for hoodie clustering",
+          unspecifiedDefaultValue = "1") final String parallelism,
+      @CliOption(key = "sparkMemory", help = "Spark executor memory",
+          unspecifiedDefaultValue = "4G") final String sparkMemory,
+      @CliOption(key = "retry", help = "Number of retries",
+          unspecifiedDefaultValue = "1") final String retry,
+      @CliOption(key = "clusteringInstant", help = "Clustering instant time",
+          mandatory = true) final String clusteringInstantTime,
+      @CliOption(key = "propsFilePath", help = "path to properties file on localfs or dfs with configurations for hoodie client for compacting",
+          unspecifiedDefaultValue = "") final String propsFilePath,
+      @CliOption(key = "hoodieConfigs", help = "Any configuration that can be set in the properties file can be passed here in the form of an array",
+          unspecifiedDefaultValue = "") final String[] configs
+  ) throws Exception {
+    HoodieTableMetaClient client = HoodieCLI.getTableMetaClient();
+    boolean initialized = HoodieCLI.initConf();
+    HoodieCLI.initFS(initialized);
+
+    String sparkPropertiesPath =
+        Utils.getDefaultPropertiesFile(JavaConverters.mapAsScalaMapConverter(System.getenv()).asScala());
+    SparkLauncher sparkLauncher = SparkUtil.initLauncher(sparkPropertiesPath);
+    sparkLauncher.addAppArgs(SparkCommand.CLUSTERING_RUN.toString(), client.getBasePath(),
+        client.getTableConfig().getTableName(), clusteringInstantTime, parallelism, sparkMemory, retry, propsFilePath);
+    UtilHelpers.validateAndAddProperties(configs, sparkLauncher);
+    Process process = sparkLauncher.launch();
+    InputStreamConsumer.captureOutput(process);
+    int exitCode = process.waitFor();
+    if (exitCode != 0) {
+      return "Failed to run clustering for " + clusteringInstantTime;
+    }
+    return "Succeeded to run clustering for " + clusteringInstantTime;
+  }
+}

hudi-cli/src/main/java/org/apache/hudi/cli/commands/SparkMain.java

@@ -41,6 +41,7 @@ import org.apache.hudi.table.upgrade.SparkUpgradeDowngrade;
 import org.apache.hudi.utilities.HDFSParquetImporter;
 import org.apache.hudi.utilities.HDFSParquetImporter.Config;
 import org.apache.hudi.utilities.HoodieCleaner;
+import org.apache.hudi.utilities.HoodieClusteringJob;
 import org.apache.hudi.utilities.HoodieCompactionAdminTool;
 import org.apache.hudi.utilities.HoodieCompactionAdminTool.Operation;
 import org.apache.hudi.utilities.HoodieCompactor;
@@ -70,7 +71,8 @@ public class SparkMain {
    */
   enum SparkCommand {
     BOOTSTRAP, ROLLBACK, DEDUPLICATE, ROLLBACK_TO_SAVEPOINT, SAVEPOINT, IMPORT, UPSERT, COMPACT_SCHEDULE, COMPACT_RUN,
-    COMPACT_UNSCHEDULE_PLAN, COMPACT_UNSCHEDULE_FILE, COMPACT_VALIDATE, COMPACT_REPAIR, CLEAN, DELETE_SAVEPOINT, UPGRADE, DOWNGRADE
+    COMPACT_UNSCHEDULE_PLAN, COMPACT_UNSCHEDULE_FILE, COMPACT_VALIDATE, COMPACT_REPAIR, CLUSTERING_SCHEDULE,
+    CLUSTERING_RUN, CLEAN, DELETE_SAVEPOINT, UPGRADE, DOWNGRADE
   }
 
   public static void main(String[] args) throws Exception {
@@ -157,6 +159,31 @@ public class SparkMain {
                   Boolean.parseBoolean(args[7]), Boolean.parseBoolean(args[8]));
           returnCode = 0;
           break;
+        case CLUSTERING_RUN:
+          assert (args.length >= 8);
+          propsFilePath = null;
+          if (!StringUtils.isNullOrEmpty(args[7])) {
+            propsFilePath = args[7];
+          }
+          configs = new ArrayList<>();
+          if (args.length > 8) {
+            configs.addAll(Arrays.asList(args).subList(8, args.length));
+          }
+          returnCode = cluster(jsc, args[1], args[2], args[3], Integer.parseInt(args[4]), args[5],
+              Integer.parseInt(args[6]), false, propsFilePath, configs);
+          break;
+        case CLUSTERING_SCHEDULE:
+          assert (args.length >= 6);
+          propsFilePath = null;
+          if (!StringUtils.isNullOrEmpty(args[5])) {
+            propsFilePath = args[5];
+          }
+          configs = new ArrayList<>();
+          if (args.length > 6) {
+            configs.addAll(Arrays.asList(args).subList(6, args.length));
+          }
+          returnCode = cluster(jsc, args[1], args[2], args[3], 1, args[4], 0, true, propsFilePath, configs);
+          break;
         case CLEAN:
           assert (args.length >= 5);
           propsFilePath = null;
@@ -302,6 +329,20 @@ public class SparkMain {
     return new HoodieCompactor(jsc, cfg).compact(retry);
   }
 
+  private static int cluster(JavaSparkContext jsc, String basePath, String tableName, String clusteringInstant,
+      int parallelism, String sparkMemory, int retry, boolean schedule, String propsFilePath, List<String> configs) {
+    HoodieClusteringJob.Config cfg = new HoodieClusteringJob.Config();
+    cfg.basePath = basePath;
+    cfg.tableName = tableName;
+    cfg.clusteringInstantTime = clusteringInstant;
+    cfg.parallelism = parallelism;
+    cfg.runSchedule = schedule;
+    cfg.propsFilePath = propsFilePath;
+    cfg.configs = configs;
+    jsc.getConf().set("spark.executor.memory", sparkMemory);
+    return new HoodieClusteringJob(jsc, cfg).cluster(retry);
+  }
+
   private static int deduplicatePartitionPath(JavaSparkContext jsc, String duplicatedPartitionPath,
       String repairedOutputPath, String basePath, boolean dryRun, String dedupeType) {
     DedupeSparkJob job = new DedupeSparkJob(basePath, duplicatedPartitionPath, repairedOutputPath, new SQLContext(jsc),

hudi-utilities/src/main/java/org/apache/hudi/utilities/HoodieClusteringJob.java

@@ -164,7 +164,10 @@ public class HoodieClusteringJob {
     String schemaStr = getSchemaFromLatestInstant();
     SparkRDDWriteClient client =
         UtilHelpers.createHoodieClient(jsc, cfg.basePath, schemaStr, cfg.parallelism, Option.empty(), props);
+    if (cfg.clusteringInstantTime != null) {
+      client.scheduleClusteringAtInstant(cfg.clusteringInstantTime, Option.empty());
+      return Option.of(cfg.clusteringInstantTime);
+    }
     return client.scheduleClustering(Option.empty());
   }
-
 }