nsivabalan commented on a change in pull request #2915: URL: https://github.com/apache/hudi/pull/2915#discussion_r643894403
########## File path: hudi-utilities/src/main/java/org/apache/hudi/utilities/sources/JdbcSource.java ########## @@ -0,0 +1,339 @@ +/* + * 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.utilities.sources; + +import org.apache.hudi.DataSourceUtils; +import org.apache.hudi.common.config.TypedProperties; +import org.apache.hudi.common.util.Option; +import org.apache.hudi.common.util.StringUtils; +import org.apache.hudi.common.util.collection.Pair; +import org.apache.hudi.exception.HoodieException; +import org.apache.hudi.utilities.SqlQueryBuilder; +import org.apache.hudi.utilities.schema.SchemaProvider; + +import org.apache.hadoop.fs.FSDataInputStream; +import org.apache.hadoop.fs.FileSystem; +import org.apache.hadoop.fs.Path; +import org.apache.hadoop.io.IOUtils; +import org.apache.log4j.LogManager; +import org.apache.log4j.Logger; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.sql.Column; +import org.apache.spark.sql.DataFrameReader; +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.Row; +import org.apache.spark.sql.SparkSession; +import org.apache.spark.sql.functions; +import org.apache.spark.sql.types.DataTypes; +import org.apache.spark.storage.StorageLevel; + +import java.net.URI; +import java.util.Arrays; +import java.util.Collections; +import java.util.List; +import java.util.Set; + +/** + * Reads data from RDBMS data sources. + */ + +public class JdbcSource extends RowSource { + + private static final Logger LOG = LogManager.getLogger(JdbcSource.class); + private static final List<String> DB_LIMIT_CLAUSE = Arrays.asList("mysql", "postgresql", "h2"); + private static final String URI_JDBC_PREFIX = "jdbc:"; + + public JdbcSource(TypedProperties props, JavaSparkContext sparkContext, SparkSession sparkSession, + SchemaProvider schemaProvider) { + super(props, sparkContext, sparkSession, schemaProvider); + } + + /** + * Validates all user properties and prepares the {@link DataFrameReader} to read from RDBMS. + * + * @param session The {@link SparkSession}. + * @param properties The JDBC connection properties and data source options. + * @return The {@link DataFrameReader} to read from RDBMS + * @throws HoodieException + */ + private static DataFrameReader validatePropsAndGetDataFrameReader(final SparkSession session, + final TypedProperties properties) + throws HoodieException { + DataFrameReader dataFrameReader; + FSDataInputStream passwordFileStream = null; + try { + dataFrameReader = session.read().format("jdbc"); + dataFrameReader = dataFrameReader.option(Config.URL_PROP, properties.getString(Config.URL)); + dataFrameReader = dataFrameReader.option(Config.USER_PROP, properties.getString(Config.USER)); + dataFrameReader = dataFrameReader.option(Config.DRIVER_PROP, properties.getString(Config.DRIVER_CLASS)); + dataFrameReader = dataFrameReader + .option(Config.RDBMS_TABLE_PROP, properties.getString(Config.RDBMS_TABLE_NAME)); + + if (properties.containsKey(Config.PASSWORD)) { + LOG.info("Reading JDBC password from properties file...."); + dataFrameReader = dataFrameReader.option(Config.PASSWORD_PROP, properties.getString(Config.PASSWORD)); + } else if (properties.containsKey(Config.PASSWORD_FILE) + && !StringUtils.isNullOrEmpty(properties.getString(Config.PASSWORD_FILE))) { + LOG.info(String.format("Reading JDBC password from password file %s", properties.getString(Config.PASSWORD_FILE))); + FileSystem fileSystem = FileSystem.get(session.sparkContext().hadoopConfiguration()); + passwordFileStream = fileSystem.open(new Path(properties.getString(Config.PASSWORD_FILE))); + byte[] bytes = new byte[passwordFileStream.available()]; + passwordFileStream.read(bytes); + dataFrameReader = dataFrameReader.option(Config.PASSWORD_PROP, new String(bytes)); + } else { + throw new IllegalArgumentException(String.format("JDBCSource needs either a %s or %s to connect to RDBMS " + + "datasource", Config.PASSWORD_FILE, Config.PASSWORD)); + } + + addExtraJdbcOptions(properties, dataFrameReader); + + if (properties.getBoolean(Config.IS_INCREMENTAL)) { + DataSourceUtils.checkRequiredProperties(properties, Collections.singletonList(Config.INCREMENTAL_COLUMN)); + } + return dataFrameReader; + } catch (Exception e) { + throw new HoodieException(e); + } finally { + IOUtils.closeStream(passwordFileStream); + } + } + + /** + * Accepts spark JDBC options from the user in terms of EXTRA_OPTIONS adds them to {@link DataFrameReader} Example: In + * a normal spark code you would do something like: session.read.format('jdbc') .option(fetchSize,1000) + * .option(timestampFormat,"yyyy-mm-dd hh:mm:ss") + * <p> + * The way to pass these properties to HUDI is through the config file. Any property starting with + * hoodie.deltastreamer.jdbc.extra.options. will be added. + * <p> + * Example: hoodie.deltastreamer.jdbc.extra.options.fetchSize=100 + * hoodie.deltastreamer.jdbc.extra.options.upperBound=1 + * hoodie.deltastreamer.jdbc.extra.options.lowerBound=100 + * + * @param properties The JDBC connection properties and data source options. + * @param dataFrameReader The {@link DataFrameReader} to which data source options will be added. + */ + private static void addExtraJdbcOptions(TypedProperties properties, DataFrameReader dataFrameReader) { + Set<Object> objects = properties.keySet(); + for (Object property : objects) { + String prop = property.toString(); + if (prop.startsWith(Config.EXTRA_OPTIONS)) { + String key = String.join("", prop.split(Config.EXTRA_OPTIONS)); + String value = properties.getString(prop); + if (!StringUtils.isNullOrEmpty(value)) { + LOG.info(String.format("Adding %s -> %s to jdbc options", key, value)); + dataFrameReader.option(key, value); + } + } + } + } + + @Override + protected Pair<Option<Dataset<Row>>, String> fetchNextBatch(Option<String> lastCkptStr, long sourceLimit) throws HoodieException { + try { + DataSourceUtils.checkRequiredProperties(props, Arrays.asList(Config.URL, Config.DRIVER_CLASS, Config.USER, Config.RDBMS_TABLE_NAME, Config.IS_INCREMENTAL)); + return fetch(lastCkptStr, sourceLimit); + } catch (Exception e) { + LOG.error("Exception while running JDBCSource ", e); + throw new HoodieException(e); + } + } + + /** + * Decide to do a full RDBMS table scan or an incremental scan based on the lastCkptStr. If previous checkpoint + * value exists then we do an incremental scan with a PPD query or else we do a full scan. In certain cases where the + * incremental query fails, we fallback to a full scan. + * + * @param lastCkptStr Last checkpoint. + * @return The pair of {@link Dataset} and current checkpoint. + */ + private Pair<Option<Dataset<Row>>, String> fetch(Option<String> lastCkptStr, long sourceLimit) { + Dataset<Row> dataset; + if (lastCkptStr.isPresent() && !StringUtils.isNullOrEmpty(lastCkptStr.get())) { + dataset = incrementalFetch(lastCkptStr, sourceLimit); + } else { + LOG.info("No checkpoint references found. Doing a full rdbms table fetch"); + dataset = fullFetch(sourceLimit); + } + dataset.persist(StorageLevel.fromString(props.getString(Config.STORAGE_LEVEL, "MEMORY_AND_DISK_SER"))); + boolean isIncremental = props.getBoolean(Config.IS_INCREMENTAL); + Pair<Option<Dataset<Row>>, String> pair = Pair.of(Option.of(dataset), checkpoint(dataset, isIncremental, lastCkptStr)); + dataset.unpersist(); + return pair; + } + + /** + * Does an incremental scan with PPQ query prepared on the bases of previous checkpoint. + * + * @param lastCheckpoint Last checkpoint. + * Note that the records fetched will be exclusive of the last checkpoint (i.e. incremental column value > lastCheckpoint). + * @return The {@link Dataset} after incremental fetch from RDBMS. + */ + private Dataset<Row> incrementalFetch(Option<String> lastCheckpoint, long sourceLimit) { + try { + final String ppdQuery = "(%s) rdbms_table"; + final SqlQueryBuilder queryBuilder = SqlQueryBuilder.select("*") + .from(props.getString(Config.RDBMS_TABLE_NAME)) + .where(String.format(" %s > '%s'", props.getString(Config.INCREMENTAL_COLUMN), lastCheckpoint.get())); + + if (sourceLimit > 0) { + URI jdbcURI = URI.create(props.getString(Config.URL).substring(URI_JDBC_PREFIX.length())); + if (DB_LIMIT_CLAUSE.contains(jdbcURI.getScheme())) { + queryBuilder.orderBy(props.getString(Config.INCREMENTAL_COLUMN)).limit(sourceLimit); + } + } + String query = String.format(ppdQuery, queryBuilder.toString()); + LOG.info("PPD QUERY: " + query); + LOG.info(String.format("Referenced last checkpoint and prepared new predicate pushdown query for jdbc pull %s", query)); + return validatePropsAndGetDataFrameReader(sparkSession, props).option(Config.RDBMS_TABLE_PROP, query).load(); + } catch (Exception e) { + LOG.error("Error while performing an incremental fetch. Not all database support the PPD query we generate to do an incremental scan", e); + if (props.containsKey(Config.FALLBACK_TO_FULL_FETCH) && props.getBoolean(Config.FALLBACK_TO_FULL_FETCH)) { + LOG.warn("Falling back to full scan."); + return fullFetch(sourceLimit); + } + throw e; + } + } + + /** + * Does a full scan on the RDBMS data source. + * + * @return The {@link Dataset} after running full scan. + */ + private Dataset<Row> fullFetch(long sourceLimit) { + final String ppdQuery = "(%s) rdbms_table"; + final SqlQueryBuilder queryBuilder = SqlQueryBuilder.select("*") + .from(props.getString(Config.RDBMS_TABLE_NAME)); + if (sourceLimit > 0) { + URI jdbcURI = URI.create(props.getString(Config.URL).substring(URI_JDBC_PREFIX.length())); + if (DB_LIMIT_CLAUSE.contains(jdbcURI.getScheme())) { + if (props.containsKey(Config.INCREMENTAL_COLUMN)) { + queryBuilder.orderBy(props.getString(Config.INCREMENTAL_COLUMN)).limit(sourceLimit); + } else { + queryBuilder.limit(sourceLimit); + } + } + } + String query = String.format(ppdQuery, queryBuilder.toString()); + return validatePropsAndGetDataFrameReader(sparkSession, props).option(Config.RDBMS_TABLE_PROP, query).load(); + } + + private String checkpoint(Dataset<Row> rowDataset, boolean isIncremental, Option<String> lastCkptStr) { + try { + if (isIncremental) { + Column incrementalColumn = rowDataset.col(props.getString(Config.INCREMENTAL_COLUMN)); + final String max = rowDataset.agg(functions.max(incrementalColumn).cast(DataTypes.StringType)).first().getString(0); + LOG.info(String.format("Checkpointing column %s with value: %s ", incrementalColumn, max)); + if (max != null) { + return max; + } + return lastCkptStr.isPresent() && !StringUtils.isNullOrEmpty(lastCkptStr.get()) ? lastCkptStr.get() : StringUtils.EMPTY_STRING; + } else { + return StringUtils.EMPTY_STRING; + } + } catch (Exception e) { + return StringUtils.EMPTY_STRING; + } + } + + /** + * Inner class with config keys. + */ + protected static class Config { + + /** + * {@value #URL} is the jdbc url for the Hoodie datasource. + */ + private static final String URL = "hoodie.deltastreamer.jdbc.url"; + + private static final String URL_PROP = "url"; + + /** + * {@value #USER} is the username used for JDBC connection. + */ + private static final String USER = "hoodie.deltastreamer.jdbc.user"; + + /** + * {@value #USER_PROP} used internally to build jdbc params. + */ + private static final String USER_PROP = "user"; + + /** + * {@value #PASSWORD} is the password used for JDBC connection. + */ + private static final String PASSWORD = "hoodie.deltastreamer.jdbc.password"; + + /** + * {@value #PASSWORD_FILE} is the base-path for the JDBC password file. + */ + private static final String PASSWORD_FILE = "hoodie.deltastreamer.jdbc.password.file"; + + /** + * {@value #PASSWORD_PROP} used internally to build jdbc params. + */ + private static final String PASSWORD_PROP = "password"; + + /** + * {@value #DRIVER_CLASS} used for JDBC connection. + */ + private static final String DRIVER_CLASS = "hoodie.deltastreamer.jdbc.driver.class"; + + /** + * {@value #DRIVER_PROP} used internally to build jdbc params. + */ + private static final String DRIVER_PROP = "driver"; + + /** + * {@value #RDBMS_TABLE_NAME} RDBMS table to pull. + */ + private static final String RDBMS_TABLE_NAME = "hoodie.deltastreamer.jdbc.table.name"; + + /** + * {@value #RDBMS_TABLE_PROP} used internally for jdbc. + */ + private static final String RDBMS_TABLE_PROP = "dbtable"; + + /** + * {@value #INCREMENTAL_COLUMN} if ran in incremental mode, this field will be used to pull new data incrementally. + */ + private static final String INCREMENTAL_COLUMN = "hoodie.deltastreamer.jdbc.table.incremental.column.name"; + + /** + * {@value #IS_INCREMENTAL} will the JDBC source do an incremental pull? + */ + private static final String IS_INCREMENTAL = "hoodie.deltastreamer.jdbc.incremental.pull"; + + /** + * {@value #EXTRA_OPTIONS} used to set any extra options the user specifies for jdbc. + */ + private static final String EXTRA_OPTIONS = "hoodie.deltastreamer.jdbc.extra.options."; + + /** + * {@value #STORAGE_LEVEL} is used to control the persistence level. Default value: MEMORY_AND_DISK_SER. + */ + private static final String STORAGE_LEVEL = "hoodie.deltastreamer.jdbc.storage.level"; + + /** + * {@value #FALLBACK_TO_FULL_FETCH} is a boolean, which if set true, makes incremental fetch to fallback to full fetch in case of any error. + */ + private static final String FALLBACK_TO_FULL_FETCH = "hoodie.deltastreamer.jdbc.incremental.fallback_to_full"; Review comment: if you consider my other comment "incr", then you could change this config to "hoodie.deltastreamer.jdbc.incr.fallback.to.full.fetch". 1. incremental -> incr 2. replace "_" with "." 3. suffix "fetch". I mean, only (1) is debatable. but do fix other two. ########## File path: hudi-utilities/src/main/java/org/apache/hudi/utilities/sources/JdbcSource.java ########## @@ -0,0 +1,339 @@ +/* + * 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.utilities.sources; + +import org.apache.hudi.DataSourceUtils; +import org.apache.hudi.common.config.TypedProperties; +import org.apache.hudi.common.util.Option; +import org.apache.hudi.common.util.StringUtils; +import org.apache.hudi.common.util.collection.Pair; +import org.apache.hudi.exception.HoodieException; +import org.apache.hudi.utilities.SqlQueryBuilder; +import org.apache.hudi.utilities.schema.SchemaProvider; + +import org.apache.hadoop.fs.FSDataInputStream; +import org.apache.hadoop.fs.FileSystem; +import org.apache.hadoop.fs.Path; +import org.apache.hadoop.io.IOUtils; +import org.apache.log4j.LogManager; +import org.apache.log4j.Logger; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.sql.Column; +import org.apache.spark.sql.DataFrameReader; +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.Row; +import org.apache.spark.sql.SparkSession; +import org.apache.spark.sql.functions; +import org.apache.spark.sql.types.DataTypes; +import org.apache.spark.storage.StorageLevel; + +import java.net.URI; +import java.util.Arrays; +import java.util.Collections; +import java.util.List; +import java.util.Set; + +/** + * Reads data from RDBMS data sources. + */ + +public class JdbcSource extends RowSource { + + private static final Logger LOG = LogManager.getLogger(JdbcSource.class); + private static final List<String> DB_LIMIT_CLAUSE = Arrays.asList("mysql", "postgresql", "h2"); + private static final String URI_JDBC_PREFIX = "jdbc:"; + + public JdbcSource(TypedProperties props, JavaSparkContext sparkContext, SparkSession sparkSession, + SchemaProvider schemaProvider) { + super(props, sparkContext, sparkSession, schemaProvider); + } + + /** + * Validates all user properties and prepares the {@link DataFrameReader} to read from RDBMS. + * + * @param session The {@link SparkSession}. + * @param properties The JDBC connection properties and data source options. + * @return The {@link DataFrameReader} to read from RDBMS + * @throws HoodieException + */ + private static DataFrameReader validatePropsAndGetDataFrameReader(final SparkSession session, + final TypedProperties properties) + throws HoodieException { + DataFrameReader dataFrameReader; + FSDataInputStream passwordFileStream = null; + try { + dataFrameReader = session.read().format("jdbc"); + dataFrameReader = dataFrameReader.option(Config.URL_PROP, properties.getString(Config.URL)); + dataFrameReader = dataFrameReader.option(Config.USER_PROP, properties.getString(Config.USER)); + dataFrameReader = dataFrameReader.option(Config.DRIVER_PROP, properties.getString(Config.DRIVER_CLASS)); + dataFrameReader = dataFrameReader + .option(Config.RDBMS_TABLE_PROP, properties.getString(Config.RDBMS_TABLE_NAME)); + + if (properties.containsKey(Config.PASSWORD)) { + LOG.info("Reading JDBC password from properties file...."); + dataFrameReader = dataFrameReader.option(Config.PASSWORD_PROP, properties.getString(Config.PASSWORD)); + } else if (properties.containsKey(Config.PASSWORD_FILE) + && !StringUtils.isNullOrEmpty(properties.getString(Config.PASSWORD_FILE))) { + LOG.info(String.format("Reading JDBC password from password file %s", properties.getString(Config.PASSWORD_FILE))); + FileSystem fileSystem = FileSystem.get(session.sparkContext().hadoopConfiguration()); + passwordFileStream = fileSystem.open(new Path(properties.getString(Config.PASSWORD_FILE))); + byte[] bytes = new byte[passwordFileStream.available()]; + passwordFileStream.read(bytes); + dataFrameReader = dataFrameReader.option(Config.PASSWORD_PROP, new String(bytes)); + } else { + throw new IllegalArgumentException(String.format("JDBCSource needs either a %s or %s to connect to RDBMS " + + "datasource", Config.PASSWORD_FILE, Config.PASSWORD)); + } + + addExtraJdbcOptions(properties, dataFrameReader); + + if (properties.getBoolean(Config.IS_INCREMENTAL)) { + DataSourceUtils.checkRequiredProperties(properties, Collections.singletonList(Config.INCREMENTAL_COLUMN)); + } + return dataFrameReader; + } catch (Exception e) { + throw new HoodieException(e); + } finally { + IOUtils.closeStream(passwordFileStream); + } + } + + /** + * Accepts spark JDBC options from the user in terms of EXTRA_OPTIONS adds them to {@link DataFrameReader} Example: In + * a normal spark code you would do something like: session.read.format('jdbc') .option(fetchSize,1000) + * .option(timestampFormat,"yyyy-mm-dd hh:mm:ss") + * <p> + * The way to pass these properties to HUDI is through the config file. Any property starting with + * hoodie.deltastreamer.jdbc.extra.options. will be added. + * <p> + * Example: hoodie.deltastreamer.jdbc.extra.options.fetchSize=100 + * hoodie.deltastreamer.jdbc.extra.options.upperBound=1 + * hoodie.deltastreamer.jdbc.extra.options.lowerBound=100 + * + * @param properties The JDBC connection properties and data source options. + * @param dataFrameReader The {@link DataFrameReader} to which data source options will be added. + */ + private static void addExtraJdbcOptions(TypedProperties properties, DataFrameReader dataFrameReader) { + Set<Object> objects = properties.keySet(); + for (Object property : objects) { + String prop = property.toString(); + if (prop.startsWith(Config.EXTRA_OPTIONS)) { + String key = String.join("", prop.split(Config.EXTRA_OPTIONS)); + String value = properties.getString(prop); + if (!StringUtils.isNullOrEmpty(value)) { + LOG.info(String.format("Adding %s -> %s to jdbc options", key, value)); + dataFrameReader.option(key, value); + } + } + } + } + + @Override + protected Pair<Option<Dataset<Row>>, String> fetchNextBatch(Option<String> lastCkptStr, long sourceLimit) throws HoodieException { + try { + DataSourceUtils.checkRequiredProperties(props, Arrays.asList(Config.URL, Config.DRIVER_CLASS, Config.USER, Config.RDBMS_TABLE_NAME, Config.IS_INCREMENTAL)); + return fetch(lastCkptStr, sourceLimit); + } catch (Exception e) { + LOG.error("Exception while running JDBCSource ", e); + throw new HoodieException(e); + } + } + + /** + * Decide to do a full RDBMS table scan or an incremental scan based on the lastCkptStr. If previous checkpoint + * value exists then we do an incremental scan with a PPD query or else we do a full scan. In certain cases where the + * incremental query fails, we fallback to a full scan. + * + * @param lastCkptStr Last checkpoint. + * @return The pair of {@link Dataset} and current checkpoint. + */ + private Pair<Option<Dataset<Row>>, String> fetch(Option<String> lastCkptStr, long sourceLimit) { + Dataset<Row> dataset; + if (lastCkptStr.isPresent() && !StringUtils.isNullOrEmpty(lastCkptStr.get())) { + dataset = incrementalFetch(lastCkptStr, sourceLimit); + } else { + LOG.info("No checkpoint references found. Doing a full rdbms table fetch"); + dataset = fullFetch(sourceLimit); + } + dataset.persist(StorageLevel.fromString(props.getString(Config.STORAGE_LEVEL, "MEMORY_AND_DISK_SER"))); + boolean isIncremental = props.getBoolean(Config.IS_INCREMENTAL); + Pair<Option<Dataset<Row>>, String> pair = Pair.of(Option.of(dataset), checkpoint(dataset, isIncremental, lastCkptStr)); + dataset.unpersist(); + return pair; + } + + /** + * Does an incremental scan with PPQ query prepared on the bases of previous checkpoint. + * + * @param lastCheckpoint Last checkpoint. + * Note that the records fetched will be exclusive of the last checkpoint (i.e. incremental column value > lastCheckpoint). + * @return The {@link Dataset} after incremental fetch from RDBMS. + */ + private Dataset<Row> incrementalFetch(Option<String> lastCheckpoint, long sourceLimit) { + try { + final String ppdQuery = "(%s) rdbms_table"; + final SqlQueryBuilder queryBuilder = SqlQueryBuilder.select("*") + .from(props.getString(Config.RDBMS_TABLE_NAME)) + .where(String.format(" %s > '%s'", props.getString(Config.INCREMENTAL_COLUMN), lastCheckpoint.get())); + + if (sourceLimit > 0) { + URI jdbcURI = URI.create(props.getString(Config.URL).substring(URI_JDBC_PREFIX.length())); + if (DB_LIMIT_CLAUSE.contains(jdbcURI.getScheme())) { + queryBuilder.orderBy(props.getString(Config.INCREMENTAL_COLUMN)).limit(sourceLimit); + } + } + String query = String.format(ppdQuery, queryBuilder.toString()); + LOG.info("PPD QUERY: " + query); + LOG.info(String.format("Referenced last checkpoint and prepared new predicate pushdown query for jdbc pull %s", query)); + return validatePropsAndGetDataFrameReader(sparkSession, props).option(Config.RDBMS_TABLE_PROP, query).load(); + } catch (Exception e) { + LOG.error("Error while performing an incremental fetch. Not all database support the PPD query we generate to do an incremental scan", e); + if (props.containsKey(Config.FALLBACK_TO_FULL_FETCH) && props.getBoolean(Config.FALLBACK_TO_FULL_FETCH)) { + LOG.warn("Falling back to full scan."); + return fullFetch(sourceLimit); + } + throw e; + } + } + + /** + * Does a full scan on the RDBMS data source. + * + * @return The {@link Dataset} after running full scan. + */ + private Dataset<Row> fullFetch(long sourceLimit) { + final String ppdQuery = "(%s) rdbms_table"; + final SqlQueryBuilder queryBuilder = SqlQueryBuilder.select("*") + .from(props.getString(Config.RDBMS_TABLE_NAME)); + if (sourceLimit > 0) { + URI jdbcURI = URI.create(props.getString(Config.URL).substring(URI_JDBC_PREFIX.length())); + if (DB_LIMIT_CLAUSE.contains(jdbcURI.getScheme())) { + if (props.containsKey(Config.INCREMENTAL_COLUMN)) { + queryBuilder.orderBy(props.getString(Config.INCREMENTAL_COLUMN)).limit(sourceLimit); + } else { + queryBuilder.limit(sourceLimit); + } + } + } + String query = String.format(ppdQuery, queryBuilder.toString()); + return validatePropsAndGetDataFrameReader(sparkSession, props).option(Config.RDBMS_TABLE_PROP, query).load(); + } + + private String checkpoint(Dataset<Row> rowDataset, boolean isIncremental, Option<String> lastCkptStr) { + try { + if (isIncremental) { + Column incrementalColumn = rowDataset.col(props.getString(Config.INCREMENTAL_COLUMN)); + final String max = rowDataset.agg(functions.max(incrementalColumn).cast(DataTypes.StringType)).first().getString(0); + LOG.info(String.format("Checkpointing column %s with value: %s ", incrementalColumn, max)); + if (max != null) { + return max; + } + return lastCkptStr.isPresent() && !StringUtils.isNullOrEmpty(lastCkptStr.get()) ? lastCkptStr.get() : StringUtils.EMPTY_STRING; + } else { + return StringUtils.EMPTY_STRING; + } + } catch (Exception e) { + return StringUtils.EMPTY_STRING; + } + } + + /** + * Inner class with config keys. + */ + protected static class Config { + + /** + * {@value #URL} is the jdbc url for the Hoodie datasource. + */ + private static final String URL = "hoodie.deltastreamer.jdbc.url"; + + private static final String URL_PROP = "url"; + + /** + * {@value #USER} is the username used for JDBC connection. + */ + private static final String USER = "hoodie.deltastreamer.jdbc.user"; + + /** + * {@value #USER_PROP} used internally to build jdbc params. + */ + private static final String USER_PROP = "user"; + + /** + * {@value #PASSWORD} is the password used for JDBC connection. + */ + private static final String PASSWORD = "hoodie.deltastreamer.jdbc.password"; + + /** + * {@value #PASSWORD_FILE} is the base-path for the JDBC password file. + */ + private static final String PASSWORD_FILE = "hoodie.deltastreamer.jdbc.password.file"; + + /** + * {@value #PASSWORD_PROP} used internally to build jdbc params. + */ + private static final String PASSWORD_PROP = "password"; + + /** + * {@value #DRIVER_CLASS} used for JDBC connection. + */ + private static final String DRIVER_CLASS = "hoodie.deltastreamer.jdbc.driver.class"; + + /** + * {@value #DRIVER_PROP} used internally to build jdbc params. + */ + private static final String DRIVER_PROP = "driver"; + + /** + * {@value #RDBMS_TABLE_NAME} RDBMS table to pull. + */ + private static final String RDBMS_TABLE_NAME = "hoodie.deltastreamer.jdbc.table.name"; + + /** + * {@value #RDBMS_TABLE_PROP} used internally for jdbc. + */ + private static final String RDBMS_TABLE_PROP = "dbtable"; + + /** + * {@value #INCREMENTAL_COLUMN} if ran in incremental mode, this field will be used to pull new data incrementally. + */ + private static final String INCREMENTAL_COLUMN = "hoodie.deltastreamer.jdbc.table.incremental.column.name"; Review comment: for brevity purposes, can we do "incr" instead of "incremental". ########## File path: hudi-utilities/src/main/java/org/apache/hudi/utilities/sources/JdbcSource.java ########## @@ -0,0 +1,339 @@ +/* + * 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.utilities.sources; + +import org.apache.hudi.DataSourceUtils; +import org.apache.hudi.common.config.TypedProperties; +import org.apache.hudi.common.util.Option; +import org.apache.hudi.common.util.StringUtils; +import org.apache.hudi.common.util.collection.Pair; +import org.apache.hudi.exception.HoodieException; +import org.apache.hudi.utilities.SqlQueryBuilder; +import org.apache.hudi.utilities.schema.SchemaProvider; + +import org.apache.hadoop.fs.FSDataInputStream; +import org.apache.hadoop.fs.FileSystem; +import org.apache.hadoop.fs.Path; +import org.apache.hadoop.io.IOUtils; +import org.apache.log4j.LogManager; +import org.apache.log4j.Logger; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.sql.Column; +import org.apache.spark.sql.DataFrameReader; +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.Row; +import org.apache.spark.sql.SparkSession; +import org.apache.spark.sql.functions; +import org.apache.spark.sql.types.DataTypes; +import org.apache.spark.storage.StorageLevel; + +import java.net.URI; +import java.util.Arrays; +import java.util.Collections; +import java.util.List; +import java.util.Set; + +/** + * Reads data from RDBMS data sources. + */ + +public class JdbcSource extends RowSource { + + private static final Logger LOG = LogManager.getLogger(JdbcSource.class); + private static final List<String> DB_LIMIT_CLAUSE = Arrays.asList("mysql", "postgresql", "h2"); + private static final String URI_JDBC_PREFIX = "jdbc:"; + + public JdbcSource(TypedProperties props, JavaSparkContext sparkContext, SparkSession sparkSession, + SchemaProvider schemaProvider) { + super(props, sparkContext, sparkSession, schemaProvider); + } + + /** + * Validates all user properties and prepares the {@link DataFrameReader} to read from RDBMS. + * + * @param session The {@link SparkSession}. + * @param properties The JDBC connection properties and data source options. + * @return The {@link DataFrameReader} to read from RDBMS + * @throws HoodieException + */ + private static DataFrameReader validatePropsAndGetDataFrameReader(final SparkSession session, + final TypedProperties properties) + throws HoodieException { + DataFrameReader dataFrameReader; + FSDataInputStream passwordFileStream = null; + try { + dataFrameReader = session.read().format("jdbc"); + dataFrameReader = dataFrameReader.option(Config.URL_PROP, properties.getString(Config.URL)); + dataFrameReader = dataFrameReader.option(Config.USER_PROP, properties.getString(Config.USER)); + dataFrameReader = dataFrameReader.option(Config.DRIVER_PROP, properties.getString(Config.DRIVER_CLASS)); + dataFrameReader = dataFrameReader + .option(Config.RDBMS_TABLE_PROP, properties.getString(Config.RDBMS_TABLE_NAME)); + + if (properties.containsKey(Config.PASSWORD)) { + LOG.info("Reading JDBC password from properties file...."); + dataFrameReader = dataFrameReader.option(Config.PASSWORD_PROP, properties.getString(Config.PASSWORD)); + } else if (properties.containsKey(Config.PASSWORD_FILE) + && !StringUtils.isNullOrEmpty(properties.getString(Config.PASSWORD_FILE))) { + LOG.info(String.format("Reading JDBC password from password file %s", properties.getString(Config.PASSWORD_FILE))); + FileSystem fileSystem = FileSystem.get(session.sparkContext().hadoopConfiguration()); + passwordFileStream = fileSystem.open(new Path(properties.getString(Config.PASSWORD_FILE))); + byte[] bytes = new byte[passwordFileStream.available()]; + passwordFileStream.read(bytes); + dataFrameReader = dataFrameReader.option(Config.PASSWORD_PROP, new String(bytes)); + } else { + throw new IllegalArgumentException(String.format("JDBCSource needs either a %s or %s to connect to RDBMS " + + "datasource", Config.PASSWORD_FILE, Config.PASSWORD)); + } + + addExtraJdbcOptions(properties, dataFrameReader); + + if (properties.getBoolean(Config.IS_INCREMENTAL)) { + DataSourceUtils.checkRequiredProperties(properties, Collections.singletonList(Config.INCREMENTAL_COLUMN)); + } + return dataFrameReader; + } catch (Exception e) { + throw new HoodieException(e); + } finally { + IOUtils.closeStream(passwordFileStream); + } + } + + /** + * Accepts spark JDBC options from the user in terms of EXTRA_OPTIONS adds them to {@link DataFrameReader} Example: In + * a normal spark code you would do something like: session.read.format('jdbc') .option(fetchSize,1000) + * .option(timestampFormat,"yyyy-mm-dd hh:mm:ss") + * <p> + * The way to pass these properties to HUDI is through the config file. Any property starting with + * hoodie.deltastreamer.jdbc.extra.options. will be added. + * <p> + * Example: hoodie.deltastreamer.jdbc.extra.options.fetchSize=100 + * hoodie.deltastreamer.jdbc.extra.options.upperBound=1 + * hoodie.deltastreamer.jdbc.extra.options.lowerBound=100 + * + * @param properties The JDBC connection properties and data source options. + * @param dataFrameReader The {@link DataFrameReader} to which data source options will be added. + */ + private static void addExtraJdbcOptions(TypedProperties properties, DataFrameReader dataFrameReader) { + Set<Object> objects = properties.keySet(); + for (Object property : objects) { + String prop = property.toString(); + if (prop.startsWith(Config.EXTRA_OPTIONS)) { + String key = String.join("", prop.split(Config.EXTRA_OPTIONS)); + String value = properties.getString(prop); + if (!StringUtils.isNullOrEmpty(value)) { + LOG.info(String.format("Adding %s -> %s to jdbc options", key, value)); + dataFrameReader.option(key, value); + } + } + } + } + + @Override + protected Pair<Option<Dataset<Row>>, String> fetchNextBatch(Option<String> lastCkptStr, long sourceLimit) throws HoodieException { + try { + DataSourceUtils.checkRequiredProperties(props, Arrays.asList(Config.URL, Config.DRIVER_CLASS, Config.USER, Config.RDBMS_TABLE_NAME, Config.IS_INCREMENTAL)); + return fetch(lastCkptStr, sourceLimit); + } catch (Exception e) { + LOG.error("Exception while running JDBCSource ", e); + throw new HoodieException(e); + } + } + + /** + * Decide to do a full RDBMS table scan or an incremental scan based on the lastCkptStr. If previous checkpoint + * value exists then we do an incremental scan with a PPD query or else we do a full scan. In certain cases where the + * incremental query fails, we fallback to a full scan. + * + * @param lastCkptStr Last checkpoint. + * @return The pair of {@link Dataset} and current checkpoint. + */ + private Pair<Option<Dataset<Row>>, String> fetch(Option<String> lastCkptStr, long sourceLimit) { + Dataset<Row> dataset; + if (lastCkptStr.isPresent() && !StringUtils.isNullOrEmpty(lastCkptStr.get())) { + dataset = incrementalFetch(lastCkptStr, sourceLimit); + } else { + LOG.info("No checkpoint references found. Doing a full rdbms table fetch"); + dataset = fullFetch(sourceLimit); + } + dataset.persist(StorageLevel.fromString(props.getString(Config.STORAGE_LEVEL, "MEMORY_AND_DISK_SER"))); + boolean isIncremental = props.getBoolean(Config.IS_INCREMENTAL); + Pair<Option<Dataset<Row>>, String> pair = Pair.of(Option.of(dataset), checkpoint(dataset, isIncremental, lastCkptStr)); + dataset.unpersist(); + return pair; + } + + /** + * Does an incremental scan with PPQ query prepared on the bases of previous checkpoint. + * + * @param lastCheckpoint Last checkpoint. + * Note that the records fetched will be exclusive of the last checkpoint (i.e. incremental column value > lastCheckpoint). + * @return The {@link Dataset} after incremental fetch from RDBMS. + */ + private Dataset<Row> incrementalFetch(Option<String> lastCheckpoint, long sourceLimit) { + try { + final String ppdQuery = "(%s) rdbms_table"; + final SqlQueryBuilder queryBuilder = SqlQueryBuilder.select("*") + .from(props.getString(Config.RDBMS_TABLE_NAME)) + .where(String.format(" %s > '%s'", props.getString(Config.INCREMENTAL_COLUMN), lastCheckpoint.get())); + + if (sourceLimit > 0) { + URI jdbcURI = URI.create(props.getString(Config.URL).substring(URI_JDBC_PREFIX.length())); + if (DB_LIMIT_CLAUSE.contains(jdbcURI.getScheme())) { + queryBuilder.orderBy(props.getString(Config.INCREMENTAL_COLUMN)).limit(sourceLimit); + } + } + String query = String.format(ppdQuery, queryBuilder.toString()); + LOG.info("PPD QUERY: " + query); + LOG.info(String.format("Referenced last checkpoint and prepared new predicate pushdown query for jdbc pull %s", query)); + return validatePropsAndGetDataFrameReader(sparkSession, props).option(Config.RDBMS_TABLE_PROP, query).load(); + } catch (Exception e) { + LOG.error("Error while performing an incremental fetch. Not all database support the PPD query we generate to do an incremental scan", e); + if (props.containsKey(Config.FALLBACK_TO_FULL_FETCH) && props.getBoolean(Config.FALLBACK_TO_FULL_FETCH)) { + LOG.warn("Falling back to full scan."); + return fullFetch(sourceLimit); + } + throw e; + } + } + + /** + * Does a full scan on the RDBMS data source. + * + * @return The {@link Dataset} after running full scan. + */ + private Dataset<Row> fullFetch(long sourceLimit) { + final String ppdQuery = "(%s) rdbms_table"; + final SqlQueryBuilder queryBuilder = SqlQueryBuilder.select("*") + .from(props.getString(Config.RDBMS_TABLE_NAME)); + if (sourceLimit > 0) { + URI jdbcURI = URI.create(props.getString(Config.URL).substring(URI_JDBC_PREFIX.length())); + if (DB_LIMIT_CLAUSE.contains(jdbcURI.getScheme())) { + if (props.containsKey(Config.INCREMENTAL_COLUMN)) { + queryBuilder.orderBy(props.getString(Config.INCREMENTAL_COLUMN)).limit(sourceLimit); + } else { + queryBuilder.limit(sourceLimit); + } + } + } + String query = String.format(ppdQuery, queryBuilder.toString()); + return validatePropsAndGetDataFrameReader(sparkSession, props).option(Config.RDBMS_TABLE_PROP, query).load(); + } + + private String checkpoint(Dataset<Row> rowDataset, boolean isIncremental, Option<String> lastCkptStr) { + try { + if (isIncremental) { + Column incrementalColumn = rowDataset.col(props.getString(Config.INCREMENTAL_COLUMN)); + final String max = rowDataset.agg(functions.max(incrementalColumn).cast(DataTypes.StringType)).first().getString(0); + LOG.info(String.format("Checkpointing column %s with value: %s ", incrementalColumn, max)); + if (max != null) { + return max; + } + return lastCkptStr.isPresent() && !StringUtils.isNullOrEmpty(lastCkptStr.get()) ? lastCkptStr.get() : StringUtils.EMPTY_STRING; + } else { + return StringUtils.EMPTY_STRING; + } + } catch (Exception e) { + return StringUtils.EMPTY_STRING; Review comment: I thought we might throw an exception here? fallback to full fetch is controlled elsewhere right. can you please clarify. -- This is an automated message from the Apache Git Service. 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