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[SPARK-38351][TESTS] Don't use deprecate symbol API in test classes #35560

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[SPARK-38351][TESTS] Don't use deprecate symbol API in test classes #35560

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a2035fe
[SPARK-38242][SS] Sort the SparkSubmit debug output
martin-g Feb 17, 2022
59857a6
[SPARK-38351][TESTS] Scala 2.13 deprecated 'name symbols
martin-g Feb 17, 2022
e5ac031
SPARK-38351: Migrate few more entries from 'abc to Symbol("abc")
martin-g Feb 28, 2022
ba4c1ae
SPARK-38351: Replace some more 'abc with Symbol("abc")
martin-g Feb 28, 2022
58588a4
SPARK-38351: Manually format the code to not exceed 100 chars per line
martin-g Feb 28, 2022
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108 changes: 55 additions & 53 deletions sql/core/src/test/scala/org/apache/spark/sql/ColumnExpressionSuite.scala
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8 changes: 4 additions & 4 deletions sql/core/src/test/scala/org/apache/spark/sql/DataFrameSessionWindowingSuite.scala
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Expand Up @@ -83,7 +83,7 @@ class DataFrameSessionWindowingSuite extends QueryTest with SharedSparkSession
// key "b" => (19:39:27 ~ 19:39:37)

checkAnswer(
df.groupBy(session_window($"time", "10 seconds"), 'id)
df.groupBy(session_window($"time", "10 seconds"), Symbol("id"))
.agg(count("*").as("counts"), sum("value").as("sum"))
.orderBy($"session_window.start".asc)
.selectExpr("CAST(session_window.start AS STRING)", "CAST(session_window.end AS STRING)",
Expand Down Expand Up @@ -113,7 +113,7 @@ class DataFrameSessionWindowingSuite extends QueryTest with SharedSparkSession
// key "b" => (19:39:27 ~ 19:39:37)

checkAnswer(
df.groupBy(session_window($"time", "10 seconds"), 'id)
df.groupBy(session_window($"time", "10 seconds"), Symbol("id"))
.agg(count("*").as("counts"), sum_distinct(col("value")).as("sum"))
.orderBy($"session_window.start".asc)
.selectExpr("CAST(session_window.start AS STRING)", "CAST(session_window.end AS STRING)",
Expand Down Expand Up @@ -142,7 +142,7 @@ class DataFrameSessionWindowingSuite extends QueryTest with SharedSparkSession
// key "b" => (19:39:27 ~ 19:39:37)

checkAnswer(
df.groupBy(session_window($"time", "10 seconds"), 'id)
df.groupBy(session_window($"time", "10 seconds"), Symbol("id"))
.agg(sum_distinct(col("value")).as("sum"), sum_distinct(col("value2")).as("sum2"))
.orderBy($"session_window.start".asc)
.selectExpr("CAST(session_window.start AS STRING)", "CAST(session_window.end AS STRING)",
Expand Down Expand Up @@ -171,7 +171,7 @@ class DataFrameSessionWindowingSuite extends QueryTest with SharedSparkSession
// b => (19:39:27 ~ 19:39:37), (19:39:39 ~ 19:39:55)

checkAnswer(
df.groupBy(session_window($"time", "10 seconds"), 'id)
df.groupBy(session_window($"time", "10 seconds"), Symbol("id"))
.agg(count("*").as("counts"), sum("value").as("sum"))
.orderBy($"session_window.start".asc)
.selectExpr("CAST(session_window.start AS STRING)", "CAST(session_window.end AS STRING)",
Expand Down
5 changes: 3 additions & 2 deletions sql/core/src/test/scala/org/apache/spark/sql/ExplainSuite.scala
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Expand Up @@ -593,7 +593,7 @@ class ExplainSuiteAE extends ExplainSuiteHelper with EnableAdaptiveExecutionSuit
}

test("SPARK-35884: Explain should only display one plan before AQE takes effect") {
val df = (0 to 10).toDF("id").where('id > 5)
val df = (0 to 10).toDF("id").where(Symbol("id") > 5)
val modes = Seq(SimpleMode, ExtendedMode, CostMode, FormattedMode)
modes.foreach { mode =>
checkKeywordsExistsInExplain(df, mode, "AdaptiveSparkPlan")
Expand All @@ -608,7 +608,8 @@ class ExplainSuiteAE extends ExplainSuiteHelper with EnableAdaptiveExecutionSuit

test("SPARK-35884: Explain formatted with subquery") {
withTempView("t1", "t2") {
spark.range(100).select('id % 10 as "key", 'id as "value").createOrReplaceTempView("t1")
spark.range(100).select(Symbol("id") % 10 as "key", Symbol("id") as "value")
.createOrReplaceTempView("t1")
spark.range(10).createOrReplaceTempView("t2")
val query =
"""
Expand Down
67 changes: 36 additions & 31 deletions sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala
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Expand Up @@ -967,52 +967,57 @@ class FileBasedDataSourceSuite extends QueryTest

// cases when value == MAX
var v = Short.MaxValue
checkPushedFilters(format, df.where('id > v.toInt), Array(), noScan = true)
checkPushedFilters(format, df.where('id >= v.toInt), Array(sources.IsNotNull("id"),
sources.EqualTo("id", v)))
checkPushedFilters(format, df.where('id === v.toInt), Array(sources.IsNotNull("id"),
sources.EqualTo("id", v)))
checkPushedFilters(format, df.where('id <=> v.toInt),
checkPushedFilters(format, df.where(Symbol("id") > v.toInt), Array(), noScan = true)
checkPushedFilters(format, df.where(Symbol("id") >= v.toInt),
Array(sources.IsNotNull("id"), sources.EqualTo("id", v)))
checkPushedFilters(format, df.where(Symbol("id") === v.toInt),
Array(sources.IsNotNull("id"), sources.EqualTo("id", v)))
checkPushedFilters(format, df.where(Symbol("id") <=> v.toInt),
Array(sources.EqualNullSafe("id", v)))
checkPushedFilters(format, df.where('id <= v.toInt), Array(sources.IsNotNull("id")))
checkPushedFilters(format, df.where('id < v.toInt), Array(sources.IsNotNull("id"),
sources.Not(sources.EqualTo("id", v))))
checkPushedFilters(format, df.where(Symbol("id") <= v.toInt),
Array(sources.IsNotNull("id")))
checkPushedFilters(format, df.where(Symbol("id") < v.toInt),
Array(sources.IsNotNull("id"), sources.Not(sources.EqualTo("id", v))))

// cases when value > MAX
var v1: Int = positiveInt
checkPushedFilters(format, df.where('id > v1), Array(), noScan = true)
checkPushedFilters(format, df.where('id >= v1), Array(), noScan = true)
checkPushedFilters(format, df.where('id === v1), Array(), noScan = true)
checkPushedFilters(format, df.where('id <=> v1), Array(), noScan = true)
checkPushedFilters(format, df.where('id <= v1), Array(sources.IsNotNull("id")))
checkPushedFilters(format, df.where('id < v1), Array(sources.IsNotNull("id")))
checkPushedFilters(format, df.where(Symbol("id") > v1), Array(), noScan = true)
checkPushedFilters(format, df.where(Symbol("id") >= v1), Array(), noScan = true)
checkPushedFilters(format, df.where(Symbol("id") === v1), Array(), noScan = true)
checkPushedFilters(format, df.where(Symbol("id") <=> v1), Array(), noScan = true)
checkPushedFilters(format, df.where(Symbol("id") <= v1), Array(sources.IsNotNull("id")))
checkPushedFilters(format, df.where(Symbol("id") < v1), Array(sources.IsNotNull("id")))

// cases when value = MIN
v = Short.MinValue
checkPushedFilters(format, df.where(lit(v.toInt) < 'id), Array(sources.IsNotNull("id"),
sources.Not(sources.EqualTo("id", v))))
checkPushedFilters(format, df.where(lit(v.toInt) <= 'id), Array(sources.IsNotNull("id")))
checkPushedFilters(format, df.where(lit(v.toInt) === 'id), Array(sources.IsNotNull("id"),
checkPushedFilters(format, df.where(lit(v.toInt) < Symbol("id")),
Array(sources.IsNotNull("id"), sources.Not(sources.EqualTo("id", v))))
checkPushedFilters(format, df.where(lit(v.toInt) <= Symbol("id")),
Array(sources.IsNotNull("id")))
checkPushedFilters(format, df.where(lit(v.toInt) === Symbol("id")),
Array(sources.IsNotNull("id"),
sources.EqualTo("id", v)))
checkPushedFilters(format, df.where(lit(v.toInt) <=> 'id),
checkPushedFilters(format, df.where(lit(v.toInt) <=> Symbol("id")),
Array(sources.EqualNullSafe("id", v)))
checkPushedFilters(format, df.where(lit(v.toInt) >= 'id), Array(sources.IsNotNull("id"),
sources.EqualTo("id", v)))
checkPushedFilters(format, df.where(lit(v.toInt) > 'id), Array(), noScan = true)
checkPushedFilters(format, df.where(lit(v.toInt) >= Symbol("id")),
Array(sources.IsNotNull("id"), sources.EqualTo("id", v)))
checkPushedFilters(format, df.where(lit(v.toInt) > Symbol("id")), Array(), noScan = true)

// cases when value < MIN
v1 = negativeInt
checkPushedFilters(format, df.where(lit(v1) < 'id), Array(sources.IsNotNull("id")))
checkPushedFilters(format, df.where(lit(v1) <= 'id), Array(sources.IsNotNull("id")))
checkPushedFilters(format, df.where(lit(v1) === 'id), Array(), noScan = true)
checkPushedFilters(format, df.where(lit(v1) >= 'id), Array(), noScan = true)
checkPushedFilters(format, df.where(lit(v1) > 'id), Array(), noScan = true)
checkPushedFilters(format, df.where(lit(v1) < Symbol("id")),
Array(sources.IsNotNull("id")))
checkPushedFilters(format, df.where(lit(v1) <= Symbol("id")),
Array(sources.IsNotNull("id")))
checkPushedFilters(format, df.where(lit(v1) === Symbol("id")), Array(), noScan = true)
checkPushedFilters(format, df.where(lit(v1) >= Symbol("id")), Array(), noScan = true)
checkPushedFilters(format, df.where(lit(v1) > Symbol("id")), Array(), noScan = true)

// cases when value is within range (MIN, MAX)
checkPushedFilters(format, df.where('id > 30), Array(sources.IsNotNull("id"),
checkPushedFilters(format, df.where(Symbol("id") > 30), Array(sources.IsNotNull("id"),
sources.GreaterThan("id", 30)))
checkPushedFilters(format, df.where(lit(100) >= 'id), Array(sources.IsNotNull("id"),
sources.LessThanOrEqual("id", 100)))
checkPushedFilters(format, df.where(lit(100) >= Symbol("id")),
Array(sources.IsNotNull("id"), sources.LessThanOrEqual("id", 100)))
}
}
}
Expand Down
9 changes: 5 additions & 4 deletions sql/core/src/test/scala/org/apache/spark/sql/FileScanSuite.scala
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Expand Up @@ -85,10 +85,11 @@ trait FileScanSuiteBase extends SharedSparkSession {
val options = new CaseInsensitiveStringMap(ImmutableMap.copyOf(optionsMap))
val optionsNotEqual =
new CaseInsensitiveStringMap(ImmutableMap.copyOf(ImmutableMap.of("key2", "value2")))
val partitionFilters = Seq(And(IsNull('data.int), LessThan('data.int, 0)))
val partitionFiltersNotEqual = Seq(And(IsNull('data.int), LessThan('data.int, 1)))
val dataFilters = Seq(And(IsNull('data.int), LessThan('data.int, 0)))
val dataFiltersNotEqual = Seq(And(IsNull('data.int), LessThan('data.int, 1)))
val partitionFilters = Seq(And(IsNull(Symbol("data").int), LessThan(Symbol("data").int, 0)))
val partitionFiltersNotEqual = Seq(And(IsNull(Symbol("data").int),
LessThan(Symbol("data").int, 1)))
val dataFilters = Seq(And(IsNull(Symbol("data").int), LessThan(Symbol("data").int, 0)))
val dataFiltersNotEqual = Seq(And(IsNull(Symbol("data").int), LessThan(Symbol("data").int, 1)))

scanBuilders.foreach { case (name, scanBuilder, exclusions) =>
test(s"SPARK-33482: Test $name equals") {
Expand Down
8 changes: 4 additions & 4 deletions sql/core/src/test/scala/org/apache/spark/sql/JoinSuite.scala
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Expand Up @@ -183,7 +183,7 @@ class JoinSuite extends QueryTest with SharedSparkSession with AdaptiveSparkPlan
test("inner join where, one match per row") {
withSQLConf(SQLConf.CASE_SENSITIVE.key -> "true") {
checkAnswer(
upperCaseData.join(lowerCaseData).where('n === 'N),
upperCaseData.join(lowerCaseData).where(Symbol("n") === 'N),
Seq(
Row(1, "A", 1, "a"),
Row(2, "B", 2, "b"),
Expand Down Expand Up @@ -404,8 +404,8 @@ class JoinSuite extends QueryTest with SharedSparkSession with AdaptiveSparkPlan

test("full outer join") {
withTempView("`left`", "`right`") {
upperCaseData.where('N <= 4).createOrReplaceTempView("`left`")
upperCaseData.where('N >= 3).createOrReplaceTempView("`right`")
upperCaseData.where(Symbol("N") <= 4).createOrReplaceTempView("`left`")
upperCaseData.where(Symbol("N") >= 3).createOrReplaceTempView("`right`")

val left = UnresolvedRelation(TableIdentifier("left"))
val right = UnresolvedRelation(TableIdentifier("right"))
Expand Down Expand Up @@ -623,7 +623,7 @@ class JoinSuite extends QueryTest with SharedSparkSession with AdaptiveSparkPlan
testData.createOrReplaceTempView("B")
testData2.createOrReplaceTempView("C")
testData3.createOrReplaceTempView("D")
upperCaseData.where('N >= 3).createOrReplaceTempView("`right`")
upperCaseData.where(Symbol("N") >= 3).createOrReplaceTempView("`right`")
val cartesianQueries = Seq(
/** The following should error out since there is no explicit cross join */
"SELECT * FROM testData inner join testData2",
Expand Down
2 changes: 1 addition & 1 deletion sql/core/src/test/scala/org/apache/spark/sql/JsonFunctionsSuite.scala
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Expand Up @@ -403,7 +403,7 @@ class JsonFunctionsSuite extends QueryTest with SharedSparkSession {

test("SPARK-24709: infers schemas of json strings and pass them to from_json") {
val in = Seq("""{"a": [1, 2, 3]}""").toDS()
val out = in.select(from_json('value, schema_of_json("""{"a": [1]}""")) as "parsed")
val out = in.select(from_json(Symbol("value"), schema_of_json("""{"a": [1]}""")) as "parsed")
val expected = StructType(StructField(
"parsed",
StructType(StructField(
Expand Down
36 changes: 18 additions & 18 deletions sql/core/src/test/scala/org/apache/spark/sql/MathFunctionsSuite.scala
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Expand Up @@ -47,12 +47,12 @@ class MathFunctionsSuite extends QueryTest with SharedSparkSession {
c: Column => Column,
f: T => U): Unit = {
checkAnswer(
doubleData.select(c('a)),
doubleData.select(c(Symbol("a"))),
(1 to 10).map(n => Row(f((n * 0.2 - 1).asInstanceOf[T])))
)

checkAnswer(
doubleData.select(c('b)),
doubleData.select(c(Symbol("b"))),
(1 to 10).map(n => Row(f((-n * 0.2 + 1).asInstanceOf[T])))
)

Expand All @@ -65,13 +65,13 @@ class MathFunctionsSuite extends QueryTest with SharedSparkSession {
private def testOneToOneNonNegativeMathFunction(c: Column => Column, f: Double => Double): Unit =
{
checkAnswer(
nnDoubleData.select(c('a)),
nnDoubleData.select(c(Symbol("a"))),
(1 to 10).map(n => Row(f(n * 0.1)))
)

if (f(-1) === StrictMath.log1p(-1)) {
checkAnswer(
nnDoubleData.select(c('b)),
nnDoubleData.select(c(Symbol("b"))),
(1 to 9).map(n => Row(f(n * -0.1))) :+ Row(null)
)
}
Expand All @@ -87,12 +87,12 @@ class MathFunctionsSuite extends QueryTest with SharedSparkSession {
d: (Column, Double) => Column,
f: (Double, Double) => Double): Unit = {
checkAnswer(
nnDoubleData.select(c('a, 'a)),
nnDoubleData.select(c('a, Symbol("a"))),
nnDoubleData.collect().toSeq.map(r => Row(f(r.getDouble(0), r.getDouble(0))))
)

checkAnswer(
nnDoubleData.select(c('a, 'b)),
nnDoubleData.select(c('a, Symbol("b"))),
nnDoubleData.collect().toSeq.map(r => Row(f(r.getDouble(0), r.getDouble(1))))
)

Expand All @@ -109,7 +109,7 @@ class MathFunctionsSuite extends QueryTest with SharedSparkSession {
val nonNull = nullDoubles.collect().toSeq.filter(r => r.get(0) != null)

checkAnswer(
nullDoubles.select(c('a, 'a)).orderBy('a.asc),
nullDoubles.select(c('a, Symbol("a"))).orderBy(Symbol("a").asc),
Row(null) +: nonNull.map(r => Row(f(r.getDouble(0), r.getDouble(0))))
)
}
Expand Down Expand Up @@ -255,7 +255,7 @@ class MathFunctionsSuite extends QueryTest with SharedSparkSession {
test("factorial") {
val df = (0 to 5).map(i => (i, i)).toDF("a", "b")
checkAnswer(
df.select(factorial('a)),
df.select(factorial(Symbol("a"))),
Seq(Row(1), Row(1), Row(2), Row(6), Row(24), Row(120))
)
checkAnswer(
Expand All @@ -271,11 +271,11 @@ class MathFunctionsSuite extends QueryTest with SharedSparkSession {
test("round/bround/ceil/floor") {
val df = Seq(5, 55, 555).map(Tuple1(_)).toDF("a")
checkAnswer(
df.select(round('a), round('a, -1), round('a, -2)),
df.select(round(Symbol("a")), round('a, -1), round('a, -2)),
Seq(Row(5, 10, 0), Row(55, 60, 100), Row(555, 560, 600))
)
checkAnswer(
df.select(bround('a), bround('a, -1), bround('a, -2)),
df.select(bround(Symbol("a")), bround('a, -1), bround('a, -2)),
Seq(Row(5, 0, 0), Row(55, 60, 100), Row(555, 560, 600))
)
checkAnswer(
Expand Down Expand Up @@ -343,11 +343,11 @@ class MathFunctionsSuite extends QueryTest with SharedSparkSession {
test("round/bround/ceil/floor with data frame from a local Seq of Product") {
val df = spark.createDataFrame(Seq(Tuple1(BigDecimal("5.9")))).toDF("value")
checkAnswer(
df.withColumn("value_rounded", round('value)),
df.withColumn("value_rounded", round(Symbol("value"))),
Seq(Row(BigDecimal("5.9"), BigDecimal("6")))
)
checkAnswer(
df.withColumn("value_brounded", bround('value)),
df.withColumn("value_brounded", bround(Symbol("value"))),
Seq(Row(BigDecimal("5.9"), BigDecimal("6")))
)
checkAnswer(
Expand Down Expand Up @@ -423,10 +423,10 @@ class MathFunctionsSuite extends QueryTest with SharedSparkSession {

test("hex") {
val data = Seq((28, -28, 100800200404L, "hello")).toDF("a", "b", "c", "d")
checkAnswer(data.select(hex('a)), Seq(Row("1C")))
checkAnswer(data.select(hex('b)), Seq(Row("FFFFFFFFFFFFFFE4")))
checkAnswer(data.select(hex('c)), Seq(Row("177828FED4")))
checkAnswer(data.select(hex('d)), Seq(Row("68656C6C6F")))
checkAnswer(data.select(hex(Symbol("a"))), Seq(Row("1C")))
checkAnswer(data.select(hex(Symbol("b"))), Seq(Row("FFFFFFFFFFFFFFE4")))
checkAnswer(data.select(hex(Symbol("c"))), Seq(Row("177828FED4")))
checkAnswer(data.select(hex(Symbol("d"))), Seq(Row("68656C6C6F")))
checkAnswer(data.selectExpr("hex(a)"), Seq(Row("1C")))
checkAnswer(data.selectExpr("hex(b)"), Seq(Row("FFFFFFFFFFFFFFE4")))
checkAnswer(data.selectExpr("hex(c)"), Seq(Row("177828FED4")))
Expand All @@ -436,8 +436,8 @@ class MathFunctionsSuite extends QueryTest with SharedSparkSession {

test("unhex") {
val data = Seq(("1C", "737472696E67")).toDF("a", "b")
checkAnswer(data.select(unhex('a)), Row(Array[Byte](28.toByte)))
checkAnswer(data.select(unhex('b)), Row("string".getBytes(StandardCharsets.UTF_8)))
checkAnswer(data.select(unhex(Symbol("a"))), Row(Array[Byte](28.toByte)))
checkAnswer(data.select(unhex(Symbol("b"))), Row("string".getBytes(StandardCharsets.UTF_8)))
checkAnswer(data.selectExpr("unhex(a)"), Row(Array[Byte](28.toByte)))
checkAnswer(data.selectExpr("unhex(b)"), Row("string".getBytes(StandardCharsets.UTF_8)))
checkAnswer(data.selectExpr("""unhex("##")"""), Row(null))
Expand Down
8 changes: 5 additions & 3 deletions sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
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Expand Up @@ -3066,15 +3066,17 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark
val df = spark.read.format(format).load(dir.getCanonicalPath)
checkPushedFilters(
format,
df.where(('id < 2 and 's.contains("foo")) or ('id > 10 and 's.contains("bar"))),
df.where((Symbol("id") < 2 and Symbol("s").contains("foo")) or
(Symbol("id") > 10 and Symbol("s").contains("bar"))),
Array(sources.Or(sources.LessThan("id", 2), sources.GreaterThan("id", 10))))
checkPushedFilters(
format,
df.where('s.contains("foo") or ('id > 10 and 's.contains("bar"))),
df.where(Symbol("s").contains("foo") or
(Symbol("id") > 10 and Symbol("s").contains("bar"))),
Array.empty)
checkPushedFilters(
format,
df.where('id < 2 and not('id > 10 and 's.contains("bar"))),
df.where(Symbol("id") < 2 and not(Symbol("id") > 10 and Symbol("s").contains("bar"))),
Array(sources.IsNotNull("id"), sources.LessThan("id", 2)))
}
}
Expand Down
6 changes: 3 additions & 3 deletions sql/core/src/test/scala/org/apache/spark/sql/StatisticsCollectionSuite.scala
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Expand Up @@ -407,9 +407,9 @@ class StatisticsCollectionSuite extends StatisticsCollectionTestBase with Shared
withTable("TBL1", "TBL") {
import org.apache.spark.sql.functions._
val df = spark.range(1000L).select('id,
'id * 2 as "FLD1",
'id * 12 as "FLD2",
lit(null).cast(DoubleType) + 'id as "fld3")
Symbol("id") * 2 as "FLD1",
Symbol("id") * 12 as "FLD2",
lit(null).cast(DoubleType) + Symbol("id") as "fld3")
df.write
.mode(SaveMode.Overwrite)
.bucketBy(10, "id", "FLD1", "FLD2")
Expand Down
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