Repository: spark Updated Branches: refs/heads/master 9bbe0171c -> 35ef853b3
[SPARK-9397] DataFrame should provide an API to find source data files if applicable Certain applications would benefit from being able to inspect DataFrames that are straightforwardly produced by data sources that stem from files, and find out their source data. For example, one might want to display to a user the size of the data underlying a table, or to copy or mutate it. This PR exposes an `inputFiles` method on DataFrame which attempts to discover the source data in a best-effort manner, by inspecting HadoopFsRelations and JSONRelations. Author: Aaron Davidson <[email protected]> Closes #7717 from aarondav/paths and squashes the following commits: ff67430 [Aaron Davidson] inputFiles 0acd3ad [Aaron Davidson] [SPARK-9397] DataFrame should provide an API to find source data files if applicable Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/35ef853b Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/35ef853b Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/35ef853b Branch: refs/heads/master Commit: 35ef853b3f9d955949c464e4a0d445147e0e9a07 Parents: 9bbe017 Author: Aaron Davidson <[email protected]> Authored: Tue Jul 28 10:12:09 2015 -0700 Committer: Michael Armbrust <[email protected]> Committed: Tue Jul 28 10:12:09 2015 -0700 ---------------------------------------------------------------------- .../scala/org/apache/spark/sql/DataFrame.scala | 20 ++++++++++++++++++-- .../org/apache/spark/sql/DataFrameSuite.scala | 20 ++++++++++++++++++++ .../spark/sql/hive/HiveMetastoreCatalog.scala | 6 +++--- 3 files changed, 41 insertions(+), 5 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/35ef853b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala ---------------------------------------------------------------------- diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala index 114ab91..3ea0f9e 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala @@ -40,8 +40,9 @@ import org.apache.spark.sql.catalyst.plans.logical.{Filter, _} import org.apache.spark.sql.catalyst.plans.{Inner, JoinType} import org.apache.spark.sql.catalyst.{CatalystTypeConverters, ScalaReflection, SqlParser} import org.apache.spark.sql.execution.{EvaluatePython, ExplainCommand, LogicalRDD} -import org.apache.spark.sql.execution.datasources.CreateTableUsingAsSelect -import org.apache.spark.sql.json.JacksonGenerator +import org.apache.spark.sql.execution.datasources.{CreateTableUsingAsSelect, LogicalRelation} +import org.apache.spark.sql.json.{JacksonGenerator, JSONRelation} +import org.apache.spark.sql.sources.HadoopFsRelation import org.apache.spark.sql.types._ import org.apache.spark.storage.StorageLevel import org.apache.spark.util.Utils @@ -1546,6 +1547,21 @@ class DataFrame private[sql]( } } + /** + * Returns a best-effort snapshot of the files that compose this DataFrame. This method simply + * asks each constituent BaseRelation for its respective files and takes the union of all results. + * Depending on the source relations, this may not find all input files. Duplicates are removed. + */ + def inputFiles: Array[String] = { + val files: Seq[String] = logicalPlan.collect { + case LogicalRelation(fsBasedRelation: HadoopFsRelation) => + fsBasedRelation.paths.toSeq + case LogicalRelation(jsonRelation: JSONRelation) => + jsonRelation.path.toSeq + }.flatten + files.toSet.toArray + } + //////////////////////////////////////////////////////////////////////////// // for Python API //////////////////////////////////////////////////////////////////////////// http://git-wip-us.apache.org/repos/asf/spark/blob/35ef853b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala ---------------------------------------------------------------------- diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala index f67f2c6..3151e07 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala @@ -23,7 +23,10 @@ import scala.language.postfixOps import scala.util.Random import org.apache.spark.sql.catalyst.plans.logical.OneRowRelation +import org.apache.spark.sql.execution.datasources.LogicalRelation import org.apache.spark.sql.functions._ +import org.apache.spark.sql.json.JSONRelation +import org.apache.spark.sql.parquet.ParquetRelation import org.apache.spark.sql.types._ import org.apache.spark.sql.test.{ExamplePointUDT, ExamplePoint, SQLTestUtils} @@ -491,6 +494,23 @@ class DataFrameSuite extends QueryTest with SQLTestUtils { checkAnswer(df.select(df("key")), testData.select('key).collect().toSeq) } + test("inputFiles") { + val fakeRelation1 = new ParquetRelation(Array("/my/path", "/my/other/path"), + Some(testData.schema), None, Map.empty)(sqlContext) + val df1 = DataFrame(sqlContext, LogicalRelation(fakeRelation1)) + assert(df1.inputFiles.toSet == fakeRelation1.paths.toSet) + + val fakeRelation2 = new JSONRelation("/json/path", 1, Some(testData.schema), sqlContext) + val df2 = DataFrame(sqlContext, LogicalRelation(fakeRelation2)) + assert(df2.inputFiles.toSet == fakeRelation2.path.toSet) + + val unionDF = df1.unionAll(df2) + assert(unionDF.inputFiles.toSet == fakeRelation1.paths.toSet ++ fakeRelation2.path) + + val filtered = df1.filter("false").unionAll(df2.intersect(df2)) + assert(filtered.inputFiles.toSet == fakeRelation1.paths.toSet ++ fakeRelation2.path) + } + ignore("show") { // This test case is intended ignored, but to make sure it compiles correctly testData.select($"*").show() http://git-wip-us.apache.org/repos/asf/spark/blob/35ef853b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala ---------------------------------------------------------------------- diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala index 3180c05..a8c9b4f 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala @@ -274,9 +274,9 @@ private[hive] class HiveMetastoreCatalog(val client: ClientInterface, hive: Hive val metastoreSchema = StructType.fromAttributes(metastoreRelation.output) val mergeSchema = hive.convertMetastoreParquetWithSchemaMerging - // NOTE: Instead of passing Metastore schema directly to `ParquetRelation2`, we have to + // NOTE: Instead of passing Metastore schema directly to `ParquetRelation`, we have to // serialize the Metastore schema to JSON and pass it as a data source option because of the - // evil case insensitivity issue, which is reconciled within `ParquetRelation2`. + // evil case insensitivity issue, which is reconciled within `ParquetRelation`. val parquetOptions = Map( ParquetRelation.METASTORE_SCHEMA -> metastoreSchema.json, ParquetRelation.MERGE_SCHEMA -> mergeSchema.toString) @@ -290,7 +290,7 @@ private[hive] class HiveMetastoreCatalog(val client: ClientInterface, hive: Hive partitionSpecInMetastore: Option[PartitionSpec]): Option[LogicalRelation] = { cachedDataSourceTables.getIfPresent(tableIdentifier) match { case null => None // Cache miss - case logical@LogicalRelation(parquetRelation: ParquetRelation) => + case logical @ LogicalRelation(parquetRelation: ParquetRelation) => // If we have the same paths, same schema, and same partition spec, // we will use the cached Parquet Relation. val useCached = --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
