Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/13727#discussion_r67987384
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/test/DataFrameReaderWriterSuite.scala
---
@@ -228,4 +222,152 @@ class DataFrameReaderWriterSuite extends QueryTest
with SharedSQLContext {
}
}
}
+
+ test("load API") {
+ spark.read.format("org.apache.spark.sql.test").load()
+ spark.read.format("org.apache.spark.sql.test").load(dir)
+ spark.read.format("org.apache.spark.sql.test").load(dir, dir, dir)
+ spark.read.format("org.apache.spark.sql.test").load(Seq(dir, dir): _*)
+ Option(dir).map(spark.read.format("org.apache.spark.sql.test").load)
+ }
+
+ test("text - API and behavior regarding schema") {
+ // Writer
+ spark.createDataset(data).write.mode(SaveMode.Overwrite).text(dir)
+ testRead(spark.read.text(dir), data, textSchema)
+
+ // Reader, without user specified schema
+ testRead(spark.read.text(), Seq.empty, textSchema)
+ testRead(spark.read.text(dir, dir, dir), data ++ data ++ data,
textSchema)
+ testRead(spark.read.text(Seq(dir, dir): _*), data ++ data, textSchema)
+ // Test explicit calls to single arg method - SPARK-16009
+ testRead(Option(dir).map(spark.read.text).get, data, textSchema)
+
+ // Reader, with user specified schema, should just apply user schema
on the file data
+ testRead(spark.read.schema(userSchema).text(), Seq.empty, userSchema)
+ testRead(spark.read.schema(userSchema).text(dir), data, userSchema)
+ testRead(spark.read.schema(userSchema).text(dir, dir), data ++ data,
userSchema)
+ testRead(spark.read.schema(userSchema).text(Seq(dir, dir): _*), data
++ data, userSchema)
+ }
+
+ test("textFile - API and behavior regarding schema") {
+ spark.createDataset(data).write.mode(SaveMode.Overwrite).text(dir)
+
+ // Reader, without user specified schema
+ testRead(spark.read.textFile().toDF(), Seq.empty, textSchema)
+ testRead(spark.read.textFile(dir).toDF(), data, textSchema)
+ testRead(spark.read.textFile(dir, dir).toDF(), data ++ data,
textSchema)
+ testRead(spark.read.textFile(Seq(dir, dir): _*).toDF(), data ++ data,
textSchema)
+ // Test explicit calls to single arg method - SPARK-16009
+ testRead(Option(dir).map(spark.read.text).get, data, textSchema)
+
+ // Reader, with user specified schema, should just apply user schema
on the file data
+ val e = intercept[AnalysisException] {
spark.read.schema(userSchema).textFile() }
+ assert(e.getMessage.toLowerCase.contains("user specified schema not
supported"))
+ intercept[AnalysisException] {
spark.read.schema(userSchema).textFile(dir) }
+ intercept[AnalysisException] {
spark.read.schema(userSchema).textFile(dir, dir) }
+ intercept[AnalysisException] {
spark.read.schema(userSchema).textFile(Seq(dir, dir): _*) }
+ }
+
+ test("csv - API and behavior regarding schema") {
+ // Writer
+
spark.createDataset(data).toDF("str").write.mode(SaveMode.Overwrite).csv(dir)
+ val df = spark.read.csv(dir)
+ checkAnswer(df, spark.createDataset(data).toDF())
+ val schema = df.schema
+
+ // Reader, without user specified schema
+ intercept[IllegalArgumentException] {
+ testRead(spark.read.csv(), Seq.empty, schema)
+ }
+ testRead(spark.read.csv(dir), data, schema)
+ testRead(spark.read.csv(dir, dir), data ++ data, schema)
+ testRead(spark.read.csv(Seq(dir, dir): _*), data ++ data, schema)
+ // Test explicit calls to single arg method - SPARK-16009
+ testRead(Option(dir).map(spark.read.csv).get, data, schema)
+
+ // Reader, with user specified schema, should just apply user schema
on the file data
+ testRead(spark.read.schema(userSchema).csv(), Seq.empty, userSchema)
+ testRead(spark.read.schema(userSchema).csv(dir), data, userSchema)
+ testRead(spark.read.schema(userSchema).csv(dir, dir), data ++ data,
userSchema)
+ testRead(spark.read.schema(userSchema).csv(Seq(dir, dir): _*), data ++
data, userSchema)
+ }
+
+ test("json - API and behavior regarding schema") {
+ // Writer
+
spark.createDataset(data).toDF("str").write.mode(SaveMode.Overwrite).json(dir)
+ val df = spark.read.json(dir)
+ checkAnswer(df, spark.createDataset(data).toDF())
+ val schema = df.schema
+
+ // Reader, without user specified schema
+ intercept[AnalysisException] {
+ testRead(spark.read.json(), Seq.empty, schema)
+ }
+ testRead(spark.read.json(dir), data, schema)
+ testRead(spark.read.json(dir, dir), data ++ data, schema)
+ testRead(spark.read.json(Seq(dir, dir): _*), data ++ data, schema)
+ // Test explicit calls to single arg method - SPARK-16009
+ testRead(Option(dir).map(spark.read.json).get, data, schema)
+
+ // Reader, with user specified schema, data should be nulls as schema
in file different
+ // from user schema
+ val expData = Seq[String](null, null, null)
+ testRead(spark.read.schema(userSchema).json(), Seq.empty, userSchema)
+ testRead(spark.read.schema(userSchema).json(dir), expData, userSchema)
+ testRead(spark.read.schema(userSchema).json(dir, dir), expData ++
expData, userSchema)
+ testRead(spark.read.schema(userSchema).json(Seq(dir, dir): _*),
expData ++ expData, userSchema)
+ }
+
+ test("parquet - API and behavior regarding schema") {
+ // Writer
+
spark.createDataset(data).toDF("str").write.mode(SaveMode.Overwrite).parquet(dir)
+ val df = spark.read.parquet(dir)
+ checkAnswer(df, spark.createDataset(data).toDF())
+ val schema = df.schema
+
+ // Reader, without user specified schema
+ intercept[AnalysisException] {
+ testRead(spark.read.parquet(), Seq.empty, schema)
+ }
+ testRead(spark.read.parquet(dir), data, schema)
+ testRead(spark.read.parquet(dir, dir), data ++ data, schema)
+ testRead(spark.read.parquet(Seq(dir, dir): _*), data ++ data, schema)
+ // Test explicit calls to single arg method - SPARK-16009
+ testRead(Option(dir).map(spark.read.parquet).get, data, schema)
+
+ // Reader, with user specified schema, data should be nulls as schema
in file different
+ // from user schema
+ val expData = Seq[String](null, null, null)
+ testRead(spark.read.schema(userSchema).parquet(), Seq.empty,
userSchema)
+ testRead(spark.read.schema(userSchema).parquet(dir), expData,
userSchema)
--- End diff --
@tdas ORC behaves differently. When the user-specified schema does not
match the physical schema, it simply stops and reports an exception. Do you
think that behavior is better than returning `null` for all the rows?
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