Github user brkyvz commented on a diff in the pull request:
https://github.com/apache/spark/pull/12008#discussion_r57623602
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/TimeWindow.scala
---
@@ -0,0 +1,111 @@
+/*
+ * 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.spark.sql.catalyst.expressions
+
+import org.apache.commons.lang.StringUtils
+
+import org.apache.spark.sql.AnalysisException
+import org.apache.spark.sql.types._
+import org.apache.spark.unsafe.types.CalendarInterval
+
+case class TimeWindow(
+ originalTimeColumn: Expression,
+ private val _windowDuration: String,
+ private val _slideDuration: String,
+ private val _startTime: String) extends UnaryExpression
+ with ExpectsInputTypes
+ with Unevaluable
+ with NonSQLExpression {
+
+ override def inputTypes: Seq[AbstractDataType] =
Seq(TypeCollection(TimestampType, LongType))
+ // the time column in Timestamp format
+ lazy val timeColumn = Cast(originalTimeColumn, TimestampType)
+ override def child: Expression = timeColumn
+ override def dataType: DataType = outputType
+
+ private def outputType: StructType = StructType(Seq(
+ StructField("start", TimestampType), StructField("end",
TimestampType)))
+ lazy val output: Seq[Attribute] = outputType.toAttributes
+ def outputColumn: NamedExpression = Alias(CreateStruct(output),
"window")()
+ def windowStartCol: Attribute = output.head
+ def windowEndCol: Attribute = output.last
+
+ /**
+ * Parses the interval string for a valid time duration.
CalendarInterval expects interval
+ * strings to start with the string `interval`. For usability, we
prepend `interval` to the string
+ * if the user ommitted it.
+ * @param interval The interval string
+ * @return The interval duration in seconds. SparkSQL casts
TimestampType to Long in seconds,
+ * therefore we use seconds here as well.
+ */
+ private def getIntervalInSeconds(interval: String): Long = {
+ if (StringUtils.isBlank(interval)) {
+ throw new AnalysisException(
+ "The window duration, slide duration and start
time cannot be null.")
+ }
+ val intervalString = if (interval.startsWith("interval")) {
+ interval
+ } else {
+ "interval " + interval
+ }
+ val cal = CalendarInterval.fromString(intervalString)
+ if (cal == null) {
+ throw new AnalysisException(
+ s"The provided interval ($interval) did not
correspond to a valid interval string.")
+ }
+ (cal.months * 4 * CalendarInterval.MICROS_PER_WEEK +
cal.microseconds) / 1000000
+ }
+
+ // The window duration in seconds
--- End diff --
unfortunately yes. The conversion from LongType to TimestampType has second
precision.
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