diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
index 5210f42c557b6ebfe4f72c9a1c2c10c63baee710..cc62d5e7c8826f04dc8327a78aeb449ff9e1e898 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
@@ -1663,27 +1663,17 @@ class Analyzer(
}
}.toSeq
- // Third, for every Window Spec, we add a Window operator and set currentChild as the
- // child of it.
- var currentChild = child
- var i = 0
- while (i < groupedWindowExpressions.size) {
- val ((partitionSpec, orderSpec), windowExpressions) = groupedWindowExpressions(i)
- // Set currentChild to the newly created Window operator.
- currentChild =
- Window(
- windowExpressions,
- partitionSpec,
- orderSpec,
- currentChild)
-
- // Move to next Window Spec.
- i += 1
- }
+ // Third, we aggregate them by adding each Window operator for each Window Spec and then
+ // setting this to the child of the next Window operator.
+ val windowOps =
+ groupedWindowExpressions.foldLeft(child) {
+ case (last, ((partitionSpec, orderSpec), windowExpressions)) =>
+ Window(windowExpressions, partitionSpec, orderSpec, last)
+ }
- // Finally, we create a Project to output currentChild's output
+ // Finally, we create a Project to output windowOps's output
// newExpressionsWithWindowFunctions.
- Project(currentChild.output ++ newExpressionsWithWindowFunctions, currentChild)
+ Project(windowOps.output ++ newExpressionsWithWindowFunctions, windowOps)
} // end of addWindow
// We have to use transformDown at here to make sure the rule of
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/conditionalExpressions.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/conditionalExpressions.scala
index 1dd70bcfcfe8732ac8a0323fbb665faccbc78d79..71d4e9a3c94711dd28935f9c18c82bdd99dfb419 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/conditionalExpressions.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/conditionalExpressions.scala
@@ -125,7 +125,8 @@ abstract class CaseWhenBase(
override def eval(input: InternalRow): Any = {
var i = 0
- while (i < branches.size) {
+ val size = branches.size
+ while (i < size) {
if (java.lang.Boolean.TRUE.equals(branches(i)._1.eval(input))) {
return branches(i)._2.eval(input)
}
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ordering.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ordering.scala
index 79d2052c38a27f9724de7402bec05bb1a87e3b12..e24a3de3cfdbeb0194b781c6bcaff5612d9ba141 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ordering.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ordering.scala
@@ -31,7 +31,8 @@ class InterpretedOrdering(ordering: Seq[SortOrder]) extends Ordering[InternalRow
def compare(a: InternalRow, b: InternalRow): Int = {
var i = 0
- while (i < ordering.size) {
+ val size = ordering.size
+ while (i < size) {
val order = ordering(i)
val left = order.child.eval(a)
val right = order.child.eval(b)
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/QuantileSummaries.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/QuantileSummaries.scala
index fd62bd511fac0234245b10c2c1e55f9117e57040..27928c493d5fff198eb38521a6f544321f177424 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/QuantileSummaries.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/QuantileSummaries.scala
@@ -91,10 +91,10 @@ class QuantileSummaries(
var sampleIdx = 0
// The index of the sample currently being inserted.
var opsIdx: Int = 0
- while(opsIdx < sorted.length) {
+ while (opsIdx < sorted.length) {
val currentSample = sorted(opsIdx)
// Add all the samples before the next observation.
- while(sampleIdx < sampled.size && sampled(sampleIdx).value <= currentSample) {
+ while (sampleIdx < sampled.length && sampled(sampleIdx).value <= currentSample) {
newSamples += sampled(sampleIdx)
sampleIdx += 1
}
@@ -102,7 +102,7 @@ class QuantileSummaries(
// If it is the first one to insert, of if it is the last one
currentCount += 1
val delta =
- if (newSamples.isEmpty || (sampleIdx == sampled.size && opsIdx == sorted.length - 1)) {
+ if (newSamples.isEmpty || (sampleIdx == sampled.length && opsIdx == sorted.length - 1)) {
0
} else {
math.floor(2 * relativeError * currentCount).toInt
@@ -114,7 +114,7 @@ class QuantileSummaries(
}
// Add all the remaining existing samples
- while(sampleIdx < sampled.size) {
+ while (sampleIdx < sampled.length) {
newSamples += sampled(sampleIdx)
sampleIdx += 1
}
@@ -195,7 +195,7 @@ class QuantileSummaries(
// Minimum rank at current sample
var minRank = 0
var i = 1
- while (i < sampled.size - 1) {
+ while (i < sampled.length - 1) {
val curSample = sampled(i)
minRank += curSample.g
val maxRank = minRank + curSample.delta
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
index b09fd511a9074d8ddbff23a9f86b53044496a362..3db1d1f109fb733ba6cefe18397f6a65d69c7815 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JdbcUtils.scala
@@ -369,7 +369,7 @@ object JdbcUtils extends Logging {
val bytes = rs.getBytes(pos + 1)
var ans = 0L
var j = 0
- while (j < bytes.size) {
+ while (j < bytes.length) {
ans = 256 * ans + (255 & bytes(j))
j = j + 1
}
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala
index 4e74452f6cd12114a2e97e37020e99e5608c355c..e4b963efeaf186a0eb74f57962435d77791dbde7 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala
@@ -703,7 +703,8 @@ private[hive] trait HiveInspectors {
// 1. create the pojo (most likely) object
val result = x.create()
var i = 0
- while (i < fieldRefs.size) {
+ val size = fieldRefs.size
+ while (i < size) {
// 2. set the property for the pojo
val tpe = structType(i).dataType
x.setStructFieldData(
@@ -720,7 +721,8 @@ private[hive] trait HiveInspectors {
val row = a.asInstanceOf[InternalRow]
val result = new java.util.ArrayList[AnyRef](fieldRefs.size)
var i = 0
- while (i < fieldRefs.size) {
+ val size = fieldRefs.size
+ while (i < size) {
val tpe = structType(i).dataType
result.add(wrap(row.get(i, tpe), fieldRefs.get(i).getFieldObjectInspector, tpe))
i += 1
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala
index b4808fdbed9c920b932653e345323e65cdabb07e..ec7e53efc87f9d0c3f387440f210d7d53c3b4b3b 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala
@@ -427,7 +427,8 @@ private[hive] object HadoopTableReader extends HiveInspectors with Logging {
iterator.map { value =>
val raw = converter.convert(rawDeser.deserialize(value))
var i = 0
- while (i < fieldRefs.length) {
+ val length = fieldRefs.length
+ while (i < length) {
val fieldValue = soi.getStructFieldData(raw, fieldRefs(i))
if (fieldValue == null) {
mutableRow.setNullAt(fieldOrdinals(i))
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala
index 9347aeb8e09a8c4dd2c3e3f2f934f431ba32edef..962dd5a52ebc040cf69b0d2034814b08968b2f86 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala
@@ -153,7 +153,8 @@ private[hive] case class HiveGenericUDF(
returnInspector // Make sure initialized.
var i = 0
- while (i < children.length) {
+ val length = children.length
+ while (i < length) {
val idx = i
deferredObjects(i).asInstanceOf[DeferredObjectAdapter]
.set(() => children(idx).eval(input))
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/orc/OrcFileFormat.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/orc/OrcFileFormat.scala
index 286197b50e2290369ab0458bdae7dd5e1c429067..03b508e11aa76772bad47bd590b7cdadc697a3fa 100644
--- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/orc/OrcFileFormat.scala
+++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/orc/OrcFileFormat.scala
@@ -190,7 +190,8 @@ private[orc] class OrcSerializer(dataSchema: StructType, conf: Configuration)
row: InternalRow): Unit = {
val fieldRefs = oi.getAllStructFieldRefs
var i = 0
- while (i < fieldRefs.size) {
+ val size = fieldRefs.size
+ while (i < size) {
oi.setStructFieldData(
struct,
@@ -289,7 +290,8 @@ private[orc] object OrcRelation extends HiveInspectors {
iterator.map { value =>
val raw = deserializer.deserialize(value)
var i = 0
- while (i < fieldRefs.length) {
+ val length = fieldRefs.length
+ while (i < length) {
val fieldValue = oi.getStructFieldData(raw, fieldRefs(i))
if (fieldValue == null) {
mutableRow.setNullAt(fieldOrdinals(i))