[HUDI-3659] Reducing the validation frequency with integ tests (#5067)
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316e38c71e
@@ -89,6 +89,7 @@ public class DeltaConfig implements Serializable {
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private static String START_PARTITION = "start_partition";
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private static String DELETE_INPUT_DATA = "delete_input_data";
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private static String VALIDATE_HIVE = "validate_hive";
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private static String VALIDATE_ONCE_EVERY_ITR = "validate_once_every_itr";
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private static String EXECUTE_ITR_COUNT = "execute_itr_count";
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private static String VALIDATE_ARCHIVAL = "validate_archival";
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private static String VALIDATE_CLEAN = "validate_clean";
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@@ -216,6 +217,10 @@ public class DeltaConfig implements Serializable {
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return Boolean.valueOf(configsMap.getOrDefault(VALIDATE_HIVE, false).toString());
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}
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public int validateOnceEveryIteration() {
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return Integer.valueOf(configsMap.getOrDefault(VALIDATE_ONCE_EVERY_ITR, 1).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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@@ -74,81 +74,84 @@ public abstract class BaseValidateDatasetNode extends DagNode<Boolean> {
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@Override
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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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// listing batches to be validated
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String inputPathStr = context.getHoodieTestSuiteWriter().getCfg().inputBasePath;
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if (log.isDebugEnabled()) {
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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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log.info("fileStatuses length: " + fileStatuses.length);
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for (FileStatus fileStatus : fileStatuses) {
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log.debug("Listing all Micro batches to be validated :: " + fileStatus.getPath().toString());
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}
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}
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Dataset<Row> inputSnapshotDf = getInputDf(context, session, inputPath);
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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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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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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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int validateOnceEveryItr = config.validateOnceEveryIteration();
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int itrCountToExecute = config.getIterationCountToExecute();
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if ((itrCountToExecute != -1 && itrCountToExecute == curItrCount) ||
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(itrCountToExecute == -1 && ((curItrCount % validateOnceEveryItr) == 0))) {
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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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// listing batches to be validated
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String inputPathStr = context.getHoodieTestSuiteWriter().getCfg().inputBasePath;
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if (log.isDebugEnabled()) {
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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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log.info("fileStatuses length: " + fileStatuses.length);
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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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log.debug("Listing all Micro batches to be validated :: " + fileStatus.getPath().toString());
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}
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}
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Dataset<Row> inputSnapshotDf = getInputDf(context, session, inputPath);
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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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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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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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