vinothchandar commented on a change in pull request #917: [HUDI-251] JDBC
incremental load to HUDI with DeltaStreamer
URL: https://github.com/apache/incubator-hudi/pull/917#discussion_r331544264
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File path:
hudi-utilities/src/main/java/org/apache/hudi/utilities/sources/JDBCSource.java
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@@ -0,0 +1,233 @@
+package org.apache.hudi.utilities.sources;
+
+import java.util.Arrays;
+import org.apache.hadoop.conf.Configuration;
+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.hudi.DataSourceUtils;
+import org.apache.hudi.common.util.Option;
+import org.apache.hudi.common.util.StringUtils;
+import org.apache.hudi.common.util.TypedProperties;
+import org.apache.hudi.common.util.collection.Pair;
+import org.apache.hudi.exception.HoodieException;
+import org.apache.hudi.utilities.schema.SchemaProvider;
+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.jetbrains.annotations.NotNull;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+public class JDBCSource extends RowSource {
+
+ private static Logger LOG = LoggerFactory.getLogger(JDBCSource.class);
+
+ private final String ppdQuery = "(select * from %s where %s >= \" %s \")
rdbms_table";
+
+
+ public JDBCSource(TypedProperties props, JavaSparkContext sparkContext,
SparkSession sparkSession,
+ SchemaProvider schemaProvider) {
+ super(props, sparkContext, sparkSession, schemaProvider);
+ }
+
+ private static DataFrameReader validatePropsAndGetDataFrameReader(final
SparkSession session,
+ final TypedProperties properties)
+ throws HoodieException {
+ FSDataInputStream passwordFileStream = null;
+ try {
+ DataFrameReader 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)) {
+ if (properties.containsKey(Config.PASSWORD_FILE)) {
+ if
(!StringUtils.isNullOrEmpty(properties.getString(Config.PASSWORD_FILE))) {
+ LOG.info("Reading password for password file {}",
properties.getString(Config.PASSWORD_FILE));
+ FileSystem fileSystem = FileSystem.get(new Configuration());
+ 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("%s property cannot be null or empty",
Config.PASSWORD_FILE));
+ }
+ } else {
+ throw new IllegalArgumentException(String.format("JDBCSource needs
either a %s or %s to connect to RDBMS "
+ + "datasource", Config.PASSWORD_FILE, Config.PASSWORD));
+ }
+ } else if
(!StringUtils.isNullOrEmpty(properties.getString(Config.PASSWORD))) {
+ dataFrameReader = dataFrameReader.option(Config.PASSWORD_PROP,
properties.getString(Config.PASSWORD));
+ } else {
+ throw new IllegalArgumentException(String.format("%s cannot be null or
empty. ", Config.PASSWORD));
+ }
+ if (properties.containsKey(Config.EXTRA_OPTIONS)) {
+ if
(!StringUtils.isNullOrEmpty(properties.getString(Config.EXTRA_OPTIONS))) {
+ LOG.info("Setting {}", Config.EXTRA_OPTIONS);
+ String[] options =
properties.getString(Config.EXTRA_OPTIONS).split(",");
+ for (String option : options) {
+ if (!StringUtils.isNullOrEmpty(option)) {
+ String[] kv = option.split("=");
+ dataFrameReader = dataFrameReader.option(kv[0], kv[1]);
+ LOG.info("{} = {} has been set for JDBC pull ", kv[0], kv[1]);
+ }
+ }
+ }
+ }
+ if (properties.getBoolean(Config.IS_INCREMENTAL)) {
+ DataSourceUtils.checkRequiredProperties(properties,
Arrays.asList(Config.INCREMENTAL_COLUMN));
+ }
+ return dataFrameReader;
+ } catch (Exception e) {
+ throw new HoodieException(e);
+ } finally {
+ IOUtils.closeStream(passwordFileStream);
+ }
+ }
+
+ @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));
+
+ Option<String> beginInstant =
+ lastCkptStr.isPresent() ? lastCkptStr.get().isEmpty() ?
Option.empty() : lastCkptStr : Option.empty();
+ boolean isIncremental = props.getBoolean(Config.IS_INCREMENTAL);
+ if (beginInstant.equals(Option.empty())) {
+ LOG.info("No previous checkpoints found.. ");
+ Dataset<Row> rowDataset =
validatePropsAndGetDataFrameReader(sparkSession, props).load();
+ return sendDfAndCheckpoint(rowDataset, isIncremental);
+ } else {
+ if (StringUtils.isNullOrEmpty(beginInstant.get())) {
+ LOG.warn("Previous checkpoint entry was null or empty. Falling back
to full jdbc pull.");
+ Dataset<Row> rowDataset =
validatePropsAndGetDataFrameReader(sparkSession, props).load();
+ return sendDfAndCheckpoint(rowDataset, isIncremental);
+ } else {
+ String query = String
+ .format(ppdQuery, props.getString(Config.RDBMS_TABLE_NAME),
props.getString(Config.INCREMENTAL_COLUMN),
+ beginInstant.get());
+ LOG.info("Referenced last checkpoint and prepared new predicate
pushdown query for jdbc pull {}", query);
+ Dataset<Row> rowDataset =
validatePropsAndGetDataFrameReader(sparkSession, props)
+ .option(props.getString(Config.RDBMS_TABLE_PROP), query).load();
+ return sendDfAndCheckpoint(rowDataset, isIncremental);
+
+ }
+ }
+ } catch (Exception e) {
+ LOG.error("Exception while running JDBCSource ", e);
+ return Pair.of(Option.empty(), null);
+ }
+ }
+
+ @NotNull
+ private Pair<Option<Dataset<Row>>, String> sendDfAndCheckpoint(Dataset<Row>
rowDataset, boolean isIncremental) {
+ 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("Sending {} with checkpoint val {} ", incrementalColumn, max);
+ return Pair.of(Option.of(rowDataset), max);
+ } else {
Review comment:
makes sense.. Once you have this, we should also probably think about
generalizing across sources.. I like the fact that you can do both modes in the
same way.
Please file a JIRA for tracking this, if you also agree
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