nsivabalan commented on a change in pull request #2915: URL: https://github.com/apache/hudi/pull/2915#discussion_r627927954
########## File path: hudi-utilities/src/main/java/org/apache/hudi/utilities/sources/JdbcSource.java ########## @@ -0,0 +1,326 @@ +/* + * 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 org.jetbrains.annotations.NotNull; + +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.datasource.jdbc.extra.options. will be added. + * <p> + * Example: hoodie.datasource.jdbc.extra.options.fetchSize=100 + * hoodie.datasource.jdbc.extra.options.upperBound=1 + * hoodie.datasource.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 = (String) property; + 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) { + 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); + return Pair.of(Option.empty(), null); + } + } + + /** + * 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. + */ + @NotNull + 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(); + } + + if (props.containsKey(Config.STORAGE_LEVEL) && !StringUtils.isNullOrEmpty(props.getString(Config.STORAGE_LEVEL))) { + dataset.persist(StorageLevel.fromString(props.getString(Config.STORAGE_LEVEL))); + } else { + dataset.persist(StorageLevel.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)); + dataset.unpersist(); + + return pair; + } + + /** + * Does an incremental scan with PPQ query prepared on the bases of previous checkpoint. + * + * @param lastCheckpoint Last checkpoint Review comment: Document somewhere that during incremental fetch, this fetches rows with col val > checkpoint value (and not >=). Or in other words, exclusive. -- This is an automated message from the Apache Git Service. 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