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Original file line number Diff line number Diff line change
Expand Up @@ -108,6 +108,7 @@ class Analyzer(
GlobalAggregates ::
ResolveAggregateFunctions ::
TimeWindowing ::
ResolveInlineTables ::
TypeCoercion.typeCoercionRules ++
extendedResolutionRules : _*),
Batch("Nondeterministic", Once,
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Original file line number Diff line number Diff line change
@@ -0,0 +1,112 @@
/*
* 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.analysis

import scala.util.control.NonFatal

import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.expressions.Cast
import org.apache.spark.sql.catalyst.plans.logical.{LocalRelation, LogicalPlan}
import org.apache.spark.sql.catalyst.rules.Rule
import org.apache.spark.sql.types.{StructField, StructType}

/**
* An analyzer rule that replaces [[UnresolvedInlineTable]] with [[LocalRelation]].
*/
object ResolveInlineTables extends Rule[LogicalPlan] {
override def apply(plan: LogicalPlan): LogicalPlan = plan transformUp {
case table: UnresolvedInlineTable if table.expressionsResolved =>
validateInputDimension(table)
validateInputEvaluable(table)
convert(table)
}

/**
* Validates the input data dimension:
* 1. All rows have the same cardinality.
* 2. The number of column aliases defined is consistent with the number of columns in data.
*
* This is package visible for unit testing.
*/
private[analysis] def validateInputDimension(table: UnresolvedInlineTable): Unit = {
if (table.rows.nonEmpty) {
val numCols = table.names.size
table.rows.zipWithIndex.foreach { case (row, ri) =>
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shall we just get the table.names.size first and iterate the rows?

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That's a good idea. Let me do that.

if (row.size != numCols) {
table.failAnalysis(s"expected $numCols columns but found ${row.size} columns in row $ri")
}
}
}
}

/**
* Validates that all inline table data are valid expressions that can be evaluated
* (in this they must be foldable).
*
* This is package visible for unit testing.
*/
private[analysis] def validateInputEvaluable(table: UnresolvedInlineTable): Unit = {
table.rows.foreach { row =>
row.foreach { e =>
// Note that nondeterministic expressions are not supported since they are not foldable.
if (!e.resolved || !e.foldable) {
e.failAnalysis(s"cannot evaluate expression ${e.sql} in inline table definition")
}
}
}
}

/**
* Convert a valid (with right shape and foldable inputs) [[UnresolvedInlineTable]]
* into a [[LocalRelation]].
*
* This function attempts to coerce inputs into consistent types.
*
* This is package visible for unit testing.
*/
private[analysis] def convert(table: UnresolvedInlineTable): LocalRelation = {
// For each column, traverse all the values and find a common data type and nullability.
val fields = table.rows.transpose.zip(table.names).map { case (column, name) =>
val inputTypes = column.map(_.dataType)
val tpe = TypeCoercion.findWiderTypeWithoutStringPromotion(inputTypes).getOrElse {
table.failAnalysis(s"incompatible types found in column $name for inline table")
}
StructField(name, tpe, nullable = column.exists(_.nullable))
}
val attributes = StructType(fields).toAttributes
assert(fields.size == table.names.size)

val newRows: Seq[InternalRow] = table.rows.map { row =>
InternalRow.fromSeq(row.zipWithIndex.map { case (e, ci) =>
val targetType = fields(ci).dataType
try {
if (e.dataType.sameType(targetType)) {
e.eval()
} else {
Cast(e, targetType).eval()
}
} catch {
case NonFatal(ex) =>
table.failAnalysis(s"failed to evaluate expression ${e.sql}: ${ex.getMessage}")
}
})
}

LocalRelation(attributes, newRows)
}
}
Original file line number Diff line number Diff line change
Expand Up @@ -150,7 +150,7 @@ object TypeCoercion {
* [[findTightestCommonType]], but can handle decimal types. If the wider decimal type exceeds
* system limitation, this rule will truncate the decimal type before return it.
*/
private def findWiderTypeWithoutStringPromotion(types: Seq[DataType]): Option[DataType] = {
def findWiderTypeWithoutStringPromotion(types: Seq[DataType]): Option[DataType] = {
types.foldLeft[Option[DataType]](Some(NullType))((r, c) => r match {
case Some(d) => findTightestCommonTypeOfTwo(d, c).orElse((d, c) match {
case (t1: DecimalType, t2: DecimalType) =>
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Original file line number Diff line number Diff line change
Expand Up @@ -50,10 +50,30 @@ case class UnresolvedRelation(
}

/**
* Holds a table-valued function call that has yet to be resolved.
* An inline table that has not been resolved yet. Once resolved, it is turned by the analyzer into
* a [[org.apache.spark.sql.catalyst.plans.logical.LocalRelation]].
*
* @param names list of column names
* @param rows expressions for the data
*/
case class UnresolvedInlineTable(
names: Seq[String],
rows: Seq[Seq[Expression]])
extends LeafNode {

lazy val expressionsResolved: Boolean = rows.forall(_.forall(_.resolved))
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This is used only once. Lets move this code into that location.

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I do want this memoized, so a lazy val is better here.

override lazy val resolved = false
override def output: Seq[Attribute] = Nil
}

/**
* A table-valued function, e.g.
* {{{
* select * from range(10);
* }}}
*/
case class UnresolvedTableValuedFunction(
functionName: String, functionArgs: Seq[Expression]) extends LeafNode {
case class UnresolvedTableValuedFunction(functionName: String, functionArgs: Seq[Expression])
extends LeafNode {

override def output: Seq[Attribute] = Nil

Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -670,39 +670,24 @@ class AstBuilder extends SqlBaseBaseVisitor[AnyRef] with Logging {
*/
override def visitInlineTable(ctx: InlineTableContext): LogicalPlan = withOrigin(ctx) {
// Get the backing expressions.
val expressions = ctx.expression.asScala.map { eCtx =>
val e = expression(eCtx)
validate(e.foldable, "All expressions in an inline table must be constants.", eCtx)
e
}

// Validate and evaluate the rows.
val (structType, structConstructor) = expressions.head.dataType match {
case st: StructType =>
(st, (e: Expression) => e)
case dt =>
val st = CreateStruct(Seq(expressions.head)).dataType
(st, (e: Expression) => CreateStruct(Seq(e)))
}
val rows = expressions.map {
case expression =>
val safe = Cast(structConstructor(expression), structType)
safe.eval().asInstanceOf[InternalRow]
val rows = ctx.expression.asScala.map { e =>
expression(e) match {
// inline table comes in two styles:
// style 1: values (1), (2), (3) -- multiple columns are supported
// style 2: values 1, 2, 3 -- only a single column is supported here
case CreateStruct(children) => children // style 1
case child => Seq(child) // style 2
}
}

// Construct attributes.
val baseAttributes = structType.toAttributes.map(_.withNullability(true))
val attributes = if (ctx.identifierList != null) {
val aliases = visitIdentifierList(ctx.identifierList)
validate(aliases.size == baseAttributes.size,
"Number of aliases must match the number of fields in an inline table.", ctx)
baseAttributes.zip(aliases).map(p => p._1.withName(p._2))
val aliases = if (ctx.identifierList != null) {
visitIdentifierList(ctx.identifierList)
} else {
baseAttributes
Seq.tabulate(rows.head.size)(i => s"col${i + 1}")
}

// Create plan and add an alias if a name has been defined.
LocalRelation(attributes, rows).optionalMap(ctx.identifier)(aliasPlan)
val table = UnresolvedInlineTable(aliases, rows)
table.optionalMap(ctx.identifier)(aliasPlan)
}

/**
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Original file line number Diff line number Diff line change
@@ -0,0 +1,101 @@
/*
* 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.analysis

import org.scalatest.BeforeAndAfter

import org.apache.spark.sql.AnalysisException
import org.apache.spark.sql.catalyst.expressions.{Literal, Rand}
import org.apache.spark.sql.catalyst.expressions.aggregate.Count
import org.apache.spark.sql.catalyst.plans.PlanTest
import org.apache.spark.sql.types.{LongType, NullType}

/**
* Unit tests for [[ResolveInlineTables]]. Note that there are also test cases defined in
* end-to-end tests (in sql/core module) for verifying the correct error messages are shown
* in negative cases.
*/
class ResolveInlineTablesSuite extends PlanTest with BeforeAndAfter {

private def lit(v: Any): Literal = Literal(v)

test("validate inputs are foldable") {
ResolveInlineTables.validateInputEvaluable(
UnresolvedInlineTable(Seq("c1", "c2"), Seq(Seq(lit(1)))))

// nondeterministic (rand) should not work
intercept[AnalysisException] {
ResolveInlineTables.validateInputEvaluable(
UnresolvedInlineTable(Seq("c1"), Seq(Seq(Rand(1)))))
}

// aggregate should not work
intercept[AnalysisException] {
ResolveInlineTables.validateInputEvaluable(
UnresolvedInlineTable(Seq("c1"), Seq(Seq(Count(lit(1))))))
}

// unresolved attribute should not work
intercept[AnalysisException] {
ResolveInlineTables.validateInputEvaluable(
UnresolvedInlineTable(Seq("c1"), Seq(Seq(UnresolvedAttribute("A")))))
}
}

test("validate input dimensions") {
ResolveInlineTables.validateInputDimension(
UnresolvedInlineTable(Seq("c1"), Seq(Seq(lit(1)), Seq(lit(2)))))

// num alias != data dimension
intercept[AnalysisException] {
ResolveInlineTables.validateInputDimension(
UnresolvedInlineTable(Seq("c1", "c2"), Seq(Seq(lit(1)), Seq(lit(2)))))
}

// num alias == data dimension, but data themselves are inconsistent
intercept[AnalysisException] {
ResolveInlineTables.validateInputDimension(
UnresolvedInlineTable(Seq("c1"), Seq(Seq(lit(1)), Seq(lit(21), lit(22)))))
}
}

test("do not fire the rule if not all expressions are resolved") {
val table = UnresolvedInlineTable(Seq("c1", "c2"), Seq(Seq(UnresolvedAttribute("A"))))
assert(ResolveInlineTables(table) == table)
}

test("convert") {
val table = UnresolvedInlineTable(Seq("c1"), Seq(Seq(lit(1)), Seq(lit(2L))))
val converted = ResolveInlineTables.convert(table)

assert(converted.output.map(_.dataType) == Seq(LongType))
assert(converted.data.size == 2)
assert(converted.data(0).getLong(0) == 1L)
assert(converted.data(1).getLong(0) == 2L)
}

test("nullability inference in convert") {
val table1 = UnresolvedInlineTable(Seq("c1"), Seq(Seq(lit(1)), Seq(lit(2L))))
val converted1 = ResolveInlineTables.convert(table1)
assert(!converted1.schema.fields(0).nullable)

val table2 = UnresolvedInlineTable(Seq("c1"), Seq(Seq(lit(1)), Seq(Literal(null, NullType))))
val converted2 = ResolveInlineTables.convert(table2)
assert(converted2.schema.fields(0).nullable)
}
}
Original file line number Diff line number Diff line change
Expand Up @@ -17,9 +17,8 @@

package org.apache.spark.sql.catalyst.parser

import org.apache.spark.sql.Row
import org.apache.spark.sql.catalyst.FunctionIdentifier
import org.apache.spark.sql.catalyst.analysis.{UnresolvedGenerator, UnresolvedTableValuedFunction}
import org.apache.spark.sql.catalyst.analysis.{UnresolvedGenerator, UnresolvedInlineTable, UnresolvedTableValuedFunction}
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.plans._
import org.apache.spark.sql.catalyst.plans.logical._
Expand Down Expand Up @@ -433,19 +432,14 @@ class PlanParserSuite extends PlanTest {
}

test("inline table") {
assertEqual("values 1, 2, 3, 4", LocalRelation.fromExternalRows(
Seq('col1.int),
Seq(1, 2, 3, 4).map(x => Row(x))))
assertEqual("values 1, 2, 3, 4",
UnresolvedInlineTable(Seq("col1"), Seq(1, 2, 3, 4).map(x => Seq(Literal(x)))))

assertEqual(
"values (1, 'a'), (2, 'b'), (3, 'c') as tbl(a, b)",
LocalRelation.fromExternalRows(
Seq('a.int, 'b.string),
Seq((1, "a"), (2, "b"), (3, "c")).map(x => Row(x._1, x._2))).as("tbl"))
intercept("values (a, 'a'), (b, 'b')",
"All expressions in an inline table must be constants.")
intercept("values (1, 'a'), (2, 'b') as tbl(a, b, c)",
"Number of aliases must match the number of fields in an inline table.")
intercept[ArrayIndexOutOfBoundsException](parsePlan("values (1, 'a'), (2, 'b', 5Y)"))
"values (1, 'a'), (2, 'b') as tbl(a, b)",
UnresolvedInlineTable(
Seq("a", "b"),
Seq(Literal(1), Literal("a")) :: Seq(Literal(2), Literal("b")) :: Nil).as("tbl"))
}

test("simple select query with !> and !<") {
Expand Down
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