[HUDI-3483] Adding insert override nodes to integ test suite and few clean ups (#4895)
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@@ -96,6 +96,8 @@ public class DeltaConfig implements Serializable {
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private static String NUM_ROLLBACKS = "num_rollbacks";
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private static String ENABLE_ROW_WRITING = "enable_row_writing";
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private static String ENABLE_METADATA_VALIDATE = "enable_metadata_validate";
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private static String VALIDATE_FULL_DATA = "validate_full_data";
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private static String DELETE_INPUT_DATA_EXCEPT_LATEST = "delete_input_data_except_latest";
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// Spark SQL Create Table
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private static String TABLE_TYPE = "table_type";
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@@ -206,10 +208,18 @@ public class DeltaConfig implements Serializable {
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return Boolean.valueOf(configsMap.getOrDefault(DELETE_INPUT_DATA, false).toString());
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}
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public boolean isDeleteInputDataExceptLatest() {
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return Boolean.valueOf(configsMap.getOrDefault(DELETE_INPUT_DATA_EXCEPT_LATEST, false).toString());
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}
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public boolean isValidateHive() {
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return Boolean.valueOf(configsMap.getOrDefault(VALIDATE_HIVE, false).toString());
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}
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public boolean isValidateFullData() {
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return Boolean.valueOf(configsMap.getOrDefault(VALIDATE_FULL_DATA, false).toString());
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}
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public int getIterationCountToExecute() {
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return Integer.valueOf(configsMap.getOrDefault(EXECUTE_ITR_COUNT, -1).toString());
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}
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@@ -19,16 +19,14 @@
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package org.apache.hudi.integ.testsuite.dag.nodes;
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import org.apache.hadoop.fs.FileStatus;
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import org.apache.hadoop.fs.FileSystem;
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import org.apache.hadoop.fs.Path;
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import org.apache.hudi.DataSourceWriteOptions;
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import org.apache.hudi.common.model.HoodieRecord;
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import org.apache.hudi.integ.testsuite.configuration.DeltaConfig;
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import org.apache.hudi.integ.testsuite.dag.ExecutionContext;
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import org.apache.hudi.integ.testsuite.schema.SchemaUtils;
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import org.apache.hadoop.fs.FileStatus;
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import org.apache.hadoop.fs.FileSystem;
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import org.apache.hadoop.fs.Path;
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import org.apache.spark.api.java.function.MapFunction;
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import org.apache.spark.api.java.function.ReduceFunction;
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import org.apache.spark.sql.Dataset;
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@@ -42,13 +40,13 @@ import org.apache.spark.sql.catalyst.expressions.Attribute;
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import org.apache.spark.sql.types.StructType;
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import org.slf4j.Logger;
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import java.util.List;
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import java.util.stream.Collectors;
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import scala.Tuple2;
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import scala.collection.JavaConversions;
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import scala.collection.JavaConverters;
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import java.util.List;
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import java.util.stream.Collectors;
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/**
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* This nodes validates contents from input path are in tact with Hudi. By default no configs are required for this node. But there is an
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* optional config "delete_input_data" that you can set for this node. If set, once validation completes, contents from inputPath are deleted. This will come in handy for long running test suites.
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@@ -78,6 +76,7 @@ public abstract class BaseValidateDatasetNode extends DagNode<Boolean> {
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public void execute(ExecutionContext context, int curItrCount) throws Exception {
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SparkSession session = SparkSession.builder().sparkContext(context.getJsc().sc()).getOrCreate();
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// todo: Fix partitioning schemes. For now, assumes data based partitioning.
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String inputPath = context.getHoodieTestSuiteWriter().getCfg().inputBasePath + "/*/*";
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log.warn("Validation using data from input path " + inputPath);
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@@ -97,46 +96,60 @@ public abstract class BaseValidateDatasetNode extends DagNode<Boolean> {
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// read from hudi and remove meta columns.
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Dataset<Row> trimmedHudiDf = getDatasetToValidate(session, context, inputSnapshotDf.schema());
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Dataset<Row> intersectionDf = inputSnapshotDf.intersect(trimmedHudiDf);
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long inputCount = inputSnapshotDf.count();
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long outputCount = trimmedHudiDf.count();
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log.debug("Input count: " + inputCount + "; output count: " + outputCount);
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// the intersected df should be same as inputDf. if not, there is some mismatch.
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if (outputCount == 0 || inputCount == 0 || inputSnapshotDf.except(intersectionDf).count() != 0) {
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log.error("Data set validation failed. Total count in hudi " + outputCount + ", input df count " + inputCount);
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throw new AssertionError("Hudi contents does not match contents input data. ");
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}
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if (config.isValidateHive()) {
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String database = context.getWriterContext().getProps().getString(DataSourceWriteOptions.HIVE_DATABASE().key());
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String tableName = context.getWriterContext().getProps().getString(DataSourceWriteOptions.HIVE_TABLE().key());
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log.warn("Validating hive table with db : " + database + " and table : " + tableName);
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session.sql("REFRESH TABLE " + database + "." + tableName);
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Dataset<Row> cowDf = session.sql("SELECT _row_key, rider, driver, begin_lat, begin_lon, end_lat, end_lon, fare, _hoodie_is_deleted, " +
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"test_suite_source_ordering_field FROM " + database + "." + tableName);
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Dataset<Row> reorderedInputDf = inputSnapshotDf.select("_row_key","rider","driver","begin_lat","begin_lon","end_lat","end_lon","fare",
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"_hoodie_is_deleted","test_suite_source_ordering_field");
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Dataset<Row> intersectedHiveDf = reorderedInputDf.intersect(cowDf);
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outputCount = trimmedHudiDf.count();
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log.warn("Input count: " + inputCount + "; output count: " + outputCount);
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// the intersected df should be same as inputDf. if not, there is some mismatch.
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if (outputCount == 0 || reorderedInputDf.except(intersectedHiveDf).count() != 0) {
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log.error("Data set validation failed for COW hive table. Total count in hudi " + outputCount + ", input df count " + inputCount);
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throw new AssertionError("Hudi hive table contents does not match contents input data. ");
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if (config.isValidateFullData()) {
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log.debug("Validating full dataset");
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Dataset<Row> exceptInputDf = inputSnapshotDf.except(trimmedHudiDf);
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Dataset<Row> exceptHudiDf = trimmedHudiDf.except(inputSnapshotDf);
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long exceptInputCount = exceptInputDf.count();
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long exceptHudiCount = exceptHudiDf.count();
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log.debug("Except input df count " + exceptInputDf + ", except hudi count " + exceptHudiCount);
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if (exceptInputCount != 0 || exceptHudiCount != 0) {
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log.error("Data set validation failed. Total count in hudi " + trimmedHudiDf.count() + ", input df count " + inputSnapshotDf.count()
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+ ". InputDf except hudi df = " + exceptInputCount + ", Hudi df except Input df " + exceptHudiCount);
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throw new AssertionError("Hudi contents does not match contents input data. ");
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}
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} else {
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Dataset<Row> intersectionDf = inputSnapshotDf.intersect(trimmedHudiDf);
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long inputCount = inputSnapshotDf.count();
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long outputCount = trimmedHudiDf.count();
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log.debug("Input count: " + inputCount + "; output count: " + outputCount);
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// the intersected df should be same as inputDf. if not, there is some mismatch.
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if (outputCount == 0 || inputCount == 0 || inputSnapshotDf.except(intersectionDf).count() != 0) {
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log.error("Data set validation failed. Total count in hudi " + outputCount + ", input df count " + inputCount);
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throw new AssertionError("Hudi contents does not match contents input data. ");
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}
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}
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// if delete input data is enabled, erase input data.
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if (config.isDeleteInputData()) {
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// clean up input data for current group of writes.
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inputPathStr = context.getHoodieTestSuiteWriter().getCfg().inputBasePath;
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FileSystem fs = new Path(inputPathStr)
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.getFileSystem(context.getHoodieTestSuiteWriter().getConfiguration());
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FileStatus[] fileStatuses = fs.listStatus(new Path(inputPathStr));
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for (FileStatus fileStatus : fileStatuses) {
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log.debug("Micro batch to be deleted " + fileStatus.getPath().toString());
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fs.delete(fileStatus.getPath(), true);
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if (config.isValidateHive()) {
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String database = context.getWriterContext().getProps().getString(DataSourceWriteOptions.HIVE_DATABASE().key());
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String tableName = context.getWriterContext().getProps().getString(DataSourceWriteOptions.HIVE_TABLE().key());
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log.warn("Validating hive table with db : " + database + " and table : " + tableName);
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session.sql("REFRESH TABLE " + database + "." + tableName);
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Dataset<Row> cowDf = session.sql("SELECT _row_key, rider, driver, begin_lat, begin_lon, end_lat, end_lon, fare, _hoodie_is_deleted, " +
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"test_suite_source_ordering_field FROM " + database + "." + tableName);
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Dataset<Row> reorderedInputDf = inputSnapshotDf.select("_row_key", "rider", "driver", "begin_lat", "begin_lon", "end_lat", "end_lon", "fare",
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"_hoodie_is_deleted", "test_suite_source_ordering_field");
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Dataset<Row> intersectedHiveDf = reorderedInputDf.intersect(cowDf);
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outputCount = trimmedHudiDf.count();
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log.warn("Input count: " + inputCount + "; output count: " + outputCount);
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// the intersected df should be same as inputDf. if not, there is some mismatch.
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if (outputCount == 0 || reorderedInputDf.except(intersectedHiveDf).count() != 0) {
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log.error("Data set validation failed for COW hive table. Total count in hudi " + outputCount + ", input df count " + inputCount);
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throw new AssertionError("Hudi hive table contents does not match contents input data. ");
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}
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}
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// if delete input data is enabled, erase input data.
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if (config.isDeleteInputData()) {
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// clean up input data for current group of writes.
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inputPathStr = context.getHoodieTestSuiteWriter().getCfg().inputBasePath;
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FileSystem fs = new Path(inputPathStr)
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.getFileSystem(context.getHoodieTestSuiteWriter().getConfiguration());
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FileStatus[] fileStatuses = fs.listStatus(new Path(inputPathStr));
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for (FileStatus fileStatus : fileStatuses) {
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log.debug("Micro batch to be deleted " + fileStatus.getPath().toString());
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fs.delete(fileStatus.getPath(), true);
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}
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}
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}
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}
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@@ -149,8 +162,8 @@ public abstract class BaseValidateDatasetNode extends DagNode<Boolean> {
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Dataset<Row> inputDf = session.read().format("avro").load(inputPath);
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ExpressionEncoder encoder = getEncoder(inputDf.schema());
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return inputDf.groupByKey(
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(MapFunction<Row, String>) value ->
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value.getAs(partitionPathField) + "+" + value.getAs(recordKeyField), Encoders.STRING())
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(MapFunction<Row, String>) value ->
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value.getAs(partitionPathField) + "+" + value.getAs(recordKeyField), Encoders.STRING())
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.reduceGroups((ReduceFunction<Row>) (v1, v2) -> {
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int ts1 = v1.getAs(SchemaUtils.SOURCE_ORDERING_FIELD);
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int ts2 = v2.getAs(SchemaUtils.SOURCE_ORDERING_FIELD);
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@@ -0,0 +1,56 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing,
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* software distributed under the License is distributed on an
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* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the
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* specific language governing permissions and limitations
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* under the License.
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*/
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package org.apache.hudi.integ.testsuite.dag.nodes;
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import org.apache.hudi.integ.testsuite.configuration.DeltaConfig;
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import org.apache.hudi.integ.testsuite.dag.ExecutionContext;
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import org.apache.hadoop.fs.FileStatus;
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import org.apache.hadoop.fs.FileSystem;
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import org.apache.hadoop.fs.Path;
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/**
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* Deletes all input except latest batch. Mostly used in insert_overwrite operations.
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*/
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public class DeleteInputDatasetNode extends DagNode<Boolean> {
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public DeleteInputDatasetNode(DeltaConfig.Config config) {
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this.config = config;
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}
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@Override
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public void execute(ExecutionContext context, int curItrCount) throws Exception {
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String latestBatch = String.valueOf(context.getWriterContext().getDeltaGenerator().getBatchId());
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if (config.isDeleteInputDataExceptLatest()) {
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String inputPathStr = context.getHoodieTestSuiteWriter().getCfg().inputBasePath;
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FileSystem fs = new Path(inputPathStr)
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.getFileSystem(context.getHoodieTestSuiteWriter().getConfiguration());
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FileStatus[] fileStatuses = fs.listStatus(new Path(inputPathStr));
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for (FileStatus fileStatus : fileStatuses) {
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if (!fileStatus.getPath().getName().equals(latestBatch)) {
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log.debug("Micro batch to be deleted " + fileStatus.getPath().toString());
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fs.delete(fileStatus.getPath(), true);
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}
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}
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}
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}
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}
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@@ -110,6 +110,10 @@ public class DeltaGenerator implements Serializable {
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return ws;
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}
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public int getBatchId() {
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return batchId;
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}
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public JavaRDD<GenericRecord> generateInserts(Config operation) {
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int numPartitions = operation.getNumInsertPartitions();
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long recordsPerPartition = operation.getNumRecordsInsert();
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@@ -54,13 +54,18 @@ class SparkInsertNode(dagNodeConfig: Config) extends DagNode[RDD[WriteStatus]] {
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context.getWriterContext.getSparkSession)
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inputDF.write.format("hudi")
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.options(DataSourceWriteOptions.translateSqlOptions(context.getWriterContext.getProps.asScala.toMap))
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.option(DataSourceWriteOptions.PRECOMBINE_FIELD.key(), "test_suite_source_ordering_field")
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.option(DataSourceWriteOptions.TABLE_NAME.key, context.getHoodieTestSuiteWriter.getCfg.targetTableName)
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.option(DataSourceWriteOptions.TABLE_TYPE.key, context.getHoodieTestSuiteWriter.getCfg.tableType)
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.option(DataSourceWriteOptions.OPERATION.key, DataSourceWriteOptions.INSERT_OPERATION_OPT_VAL)
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.option(DataSourceWriteOptions.OPERATION.key, getOperation())
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.option(DataSourceWriteOptions.COMMIT_METADATA_KEYPREFIX.key, "deltastreamer.checkpoint.key")
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.option("deltastreamer.checkpoint.key", context.getWriterContext.getHoodieTestSuiteWriter.getLastCheckpoint.orElse(""))
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.option(HoodieWriteConfig.TBL_NAME.key, context.getHoodieTestSuiteWriter.getCfg.targetTableName)
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.mode(SaveMode.Append)
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.save(context.getHoodieTestSuiteWriter.getWriteConfig.getBasePath)
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}
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def getOperation(): String = {
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DataSourceWriteOptions.INSERT_OPERATION_OPT_VAL
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}
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}
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@@ -0,0 +1,31 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing,
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* software distributed under the License is distributed on an
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* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the
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* specific language governing permissions and limitations
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* under the License.
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*/
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package org.apache.hudi.integ.testsuite.dag.nodes
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import org.apache.hudi.DataSourceWriteOptions
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import org.apache.hudi.integ.testsuite.configuration.DeltaConfig.Config
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class SparkInsertOverwriteNode(dagNodeConfig: Config) extends SparkInsertNode(dagNodeConfig) {
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override def getOperation(): String = {
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DataSourceWriteOptions.INSERT_OVERWRITE_OPERATION_OPT_VAL
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}
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}
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@@ -0,0 +1,30 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing,
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* software distributed under the License is distributed on an
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* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the
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* specific language governing permissions and limitations
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* under the License.
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*/
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package org.apache.hudi.integ.testsuite.dag.nodes
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import org.apache.hudi.DataSourceWriteOptions
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import org.apache.hudi.integ.testsuite.configuration.DeltaConfig.Config
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class SparkInsertOverwriteTableNode(dagNodeConfig: Config) extends SparkInsertNode(dagNodeConfig) {
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override def getOperation(): String = {
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DataSourceWriteOptions.INSERT_OVERWRITE_TABLE_OPERATION_OPT_VAL
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}
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}
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@@ -18,49 +18,17 @@
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package org.apache.hudi.integ.testsuite.dag.nodes
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import org.apache.hudi.client.WriteStatus
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import org.apache.hudi.config.HoodieWriteConfig
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import org.apache.hudi.DataSourceWriteOptions
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import org.apache.hudi.integ.testsuite.configuration.DeltaConfig.Config
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import org.apache.hudi.integ.testsuite.dag.ExecutionContext
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import org.apache.hudi.{AvroConversionUtils, DataSourceWriteOptions}
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import org.apache.spark.rdd.RDD
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import org.apache.spark.sql.SaveMode
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import scala.collection.JavaConverters._
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/**
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* Spark datasource based upsert node
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*
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* @param dagNodeConfig DAG node configurations.
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*/
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class SparkUpsertNode(dagNodeConfig: Config) extends DagNode[RDD[WriteStatus]] {
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class SparkUpsertNode(dagNodeConfig: Config) extends SparkInsertNode(dagNodeConfig) {
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config = dagNodeConfig
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/**
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* Execute the {@link DagNode}.
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*
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* @param context The context needed for an execution of a node.
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* @param curItrCount iteration count for executing the node.
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* @throws Exception Thrown if the execution failed.
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*/
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override def execute(context: ExecutionContext, curItrCount: Int): Unit = {
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if (!config.isDisableGenerate) {
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println("Generating input data for node {}", this.getName)
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context.getDeltaGenerator().writeRecords(context.getDeltaGenerator().generateInserts(config)).count()
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}
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val inputDF = AvroConversionUtils.createDataFrame(context.getWriterContext.getHoodieTestSuiteWriter.getNextBatch,
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context.getWriterContext.getHoodieTestSuiteWriter.getSchema,
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context.getWriterContext.getSparkSession)
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inputDF.write.format("hudi")
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.options(DataSourceWriteOptions.translateSqlOptions(context.getWriterContext.getProps.asScala.toMap))
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.option(DataSourceWriteOptions.TABLE_NAME.key, context.getHoodieTestSuiteWriter.getCfg.targetTableName)
|
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.option(DataSourceWriteOptions.TABLE_TYPE.key, context.getHoodieTestSuiteWriter.getCfg.tableType)
|
||||
.option(DataSourceWriteOptions.OPERATION.key, DataSourceWriteOptions.INSERT_OPERATION_OPT_VAL)
|
||||
.option(DataSourceWriteOptions.COMMIT_METADATA_KEYPREFIX.key, "deltastreamer.checkpoint.key")
|
||||
.option("deltastreamer.checkpoint.key", context.getWriterContext.getHoodieTestSuiteWriter.getLastCheckpoint.orElse(""))
|
||||
.option(HoodieWriteConfig.TBL_NAME.key, context.getHoodieTestSuiteWriter.getCfg.targetTableName)
|
||||
.mode(SaveMode.Append)
|
||||
.save(context.getHoodieTestSuiteWriter.getWriteConfig.getBasePath)
|
||||
override def getOperation(): String = {
|
||||
DataSourceWriteOptions.UPSERT_OPERATION_OPT_VAL
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user