vinothchandar commented on a change in pull request #1702:
URL: https://github.com/apache/hudi/pull/1702#discussion_r466223251
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/DefaultSource.scala
##########
@@ -56,29 +58,56 @@ class DefaultSource extends RelationProvider
val parameters = Map(QUERY_TYPE_OPT_KEY -> DEFAULT_QUERY_TYPE_OPT_VAL) ++
translateViewTypesToQueryTypes(optParams)
val path = parameters.get("path")
- if (path.isEmpty) {
- throw new HoodieException("'path' must be specified.")
- }
if (parameters(QUERY_TYPE_OPT_KEY).equals(QUERY_TYPE_SNAPSHOT_OPT_VAL)) {
- // this is just effectively RO view only, where `path` can contain a mix
of
- // non-hoodie/hoodie path files. set the path filter up
- sqlContext.sparkContext.hadoopConfiguration.setClass(
- "mapreduce.input.pathFilter.class",
- classOf[HoodieROTablePathFilter],
- classOf[org.apache.hadoop.fs.PathFilter])
-
- log.info("Constructing hoodie (as parquet) data source with options :" +
parameters)
- log.warn("Snapshot view not supported yet via data source, for
MERGE_ON_READ tables. " +
- "Please query the Hive table registered using Spark SQL.")
- // simply return as a regular parquet relation
- DataSource.apply(
- sparkSession = sqlContext.sparkSession,
- userSpecifiedSchema = Option(schema),
- className = "parquet",
- options = parameters)
- .resolveRelation()
+ val readPathsStr =
parameters.get(DataSourceReadOptions.READ_PATHS_OPT_KEY)
+ if (path.isEmpty && readPathsStr.isEmpty) {
+ throw new HoodieException(s"'path' or '$READ_PATHS_OPT_KEY' or both
must be specified.")
+ }
+
+ val readPaths = readPathsStr.map(p =>
p.split(",").toSeq).getOrElse(Seq())
+ val allPaths = path.map(p => Seq(p)).getOrElse(Seq()) ++ readPaths
+
+ val fs = FSUtils.getFs(allPaths.head,
sqlContext.sparkContext.hadoopConfiguration)
+ val globPaths = HudiSparkUtils.checkAndGlobPathIfNecessary(allPaths, fs)
+
+ val tablePath = DataSourceUtils.getTablePath(fs, globPaths.toArray)
+ log.info("Obtained hudi table path: " + tablePath)
+
+ val metaClient = new HoodieTableMetaClient(fs.getConf, tablePath)
+ val bootstrapIndex = BootstrapIndex.getBootstrapIndex(metaClient)
+
+ val isBootstrappedTable = bootstrapIndex.useIndex()
Review comment:
we can just check `metaClient.getTableConfig()` for the bootstrap base
path?
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/IncrementalRelation.scala
##########
@@ -92,36 +102,69 @@ class IncrementalRelation(val sqlContext: SQLContext,
override def schema: StructType = latestSchema
override def buildScan(): RDD[Row] = {
- val fileIdToFullPath = mutable.HashMap[String, String]()
+ val regularFileIdToFullPath = mutable.HashMap[String, String]()
+ var metaBootstrapFileIdToFullPath = mutable.HashMap[String, String]()
+
for (commit <- commitsToReturn) {
val metadata: HoodieCommitMetadata =
HoodieCommitMetadata.fromBytes(commitTimeline.getInstantDetails(commit)
.get, classOf[HoodieCommitMetadata])
- fileIdToFullPath ++= metadata.getFileIdAndFullPaths(basePath).toMap
+
+ if (HoodieTimeline.METADATA_BOOTSTRAP_INSTANT_TS == commit.getTimestamp)
{
Review comment:
bootstrap is one time operation done during migration. not sure if the user
wants to incrementally fetch that existing data as a single batch. Not sure
what it means to incrementally query from bootstrap instant ts? can we just
avoid this whole thing by only supporting incremental query on commit
timestamps after bootstrap?
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/DefaultSource.scala
##########
@@ -54,29 +58,54 @@ class DefaultSource extends RelationProvider
val parameters = Map(QUERY_TYPE_OPT_KEY -> DEFAULT_QUERY_TYPE_OPT_VAL) ++
translateViewTypesToQueryTypes(optParams)
val path = parameters.get("path")
- if (path.isEmpty) {
- throw new HoodieException("'path' must be specified.")
- }
if (parameters(QUERY_TYPE_OPT_KEY).equals(QUERY_TYPE_SNAPSHOT_OPT_VAL)) {
- // this is just effectively RO view only, where `path` can contain a mix
of
- // non-hoodie/hoodie path files. set the path filter up
- sqlContext.sparkContext.hadoopConfiguration.setClass(
- "mapreduce.input.pathFilter.class",
- classOf[HoodieROTablePathFilter],
- classOf[org.apache.hadoop.fs.PathFilter])
-
- log.info("Constructing hoodie (as parquet) data source with options :" +
parameters)
- log.warn("Snapshot view not supported yet via data source, for
MERGE_ON_READ tables. " +
- "Please query the Hive table registered using Spark SQL.")
- // simply return as a regular parquet relation
- DataSource.apply(
- sparkSession = sqlContext.sparkSession,
- userSpecifiedSchema = Option(schema),
- className = "parquet",
- options = parameters)
- .resolveRelation()
+ val readPathsStr =
parameters.get(DataSourceReadOptions.READ_PATHS_OPT_KEY)
Review comment:
the bootstrap.base.path is now in `hoodie.properties`. Should can we
make this transparent for the user?
##########
File path: hudi-spark/src/main/scala/org/apache/hudi/HudiBootstrapRDD.scala
##########
@@ -0,0 +1,131 @@
+/*
+ * 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
+
+import org.apache.spark.{Partition, TaskContext}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.datasources.PartitionedFile
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.vectorized.ColumnarBatch
+
+class HudiBootstrapRDD(@transient spark: SparkSession,
Review comment:
please name the classes `Hoodie` consistent with rest of the code base.
I renamed few other classes that were checked in earlier, on gary's pr
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