[SPARK-26066][SQL] Move truncatedString to sql/catalyst and add spark.sql.debug.maxToStringFields conf

core/src/main/scala/org/apache/spark/util/Utils.scala

@@ -31,7 +31,6 @@ import java.security.SecureRandom
 import java.util.{Locale, Properties, Random, UUID}
 import java.util.concurrent._
 import java.util.concurrent.TimeUnit.NANOSECONDS
-import java.util.concurrent.atomic.AtomicBoolean
 import java.util.zip.GZIPInputStream
 
 import scala.annotation.tailrec
@@ -93,53 +92,6 @@ private[spark] object Utils extends Logging {
   private val MAX_DIR_CREATION_ATTEMPTS: Int = 10
   @volatile private var localRootDirs: Array[String] = null
 
-  /**
-   * The performance overhead of creating and logging strings for wide schemas can be large. To
-   * limit the impact, we bound the number of fields to include by default. This can be overridden
-   * by setting the 'spark.debug.maxToStringFields' conf in SparkEnv.
-   */
-  val DEFAULT_MAX_TO_STRING_FIELDS = 25
-
-  private[spark] def maxNumToStringFields = {
-    if (SparkEnv.get != null) {
-      SparkEnv.get.conf.getInt("spark.debug.maxToStringFields", DEFAULT_MAX_TO_STRING_FIELDS)
-    } else {
-      DEFAULT_MAX_TO_STRING_FIELDS
-    }
-  }
-
-  /** Whether we have warned about plan string truncation yet. */
-  private val truncationWarningPrinted = new AtomicBoolean(false)
-
-  /**
-   * Format a sequence with semantics similar to calling .mkString(). Any elements beyond
-   * maxNumToStringFields will be dropped and replaced by a "... N more fields" placeholder.
-   *
-   * @return the trimmed and formatted string.
-   */
-  def truncatedString[T](
-      seq: Seq[T],
-      start: String,
-      sep: String,
-      end: String,
-      maxNumFields: Int = maxNumToStringFields): String = {
-    if (seq.length > maxNumFields) {
-      if (truncationWarningPrinted.compareAndSet(false, true)) {
-        logWarning(
-          "Truncated the string representation of a plan since it was too large. This " +
-          "behavior can be adjusted by setting 'spark.debug.maxToStringFields' in SparkEnv.conf.")
-      }
-      val numFields = math.max(0, maxNumFields - 1)
-      seq.take(numFields).mkString(
-        start, sep, sep + "... " + (seq.length - numFields) + " more fields" + end)
-    } else {
-      seq.mkString(start, sep, end)
-    }
-  }
-
-  /** Shorthand for calling truncatedString() without start or end strings. */
-  def truncatedString[T](seq: Seq[T], sep: String): String = truncatedString(seq, "", sep, "")
-
   /** Serialize an object using Java serialization */
   def serialize[T](o: T): Array[Byte] = {
     val bos = new ByteArrayOutputStream()

core/src/test/scala/org/apache/spark/util/UtilsSuite.scala

@@ -45,14 +45,6 @@ import org.apache.spark.scheduler.SparkListener
 
 class UtilsSuite extends SparkFunSuite with ResetSystemProperties with Logging {
 
-  test("truncatedString") {
-    assert(Utils.truncatedString(Nil, "[", ", ", "]", 2) == "[]")
-    assert(Utils.truncatedString(Seq(1, 2), "[", ", ", "]", 2) == "[1, 2]")
-    assert(Utils.truncatedString(Seq(1, 2, 3), "[", ", ", "]", 2) == "[1, ... 2 more fields]")
-    assert(Utils.truncatedString(Seq(1, 2, 3), "[", ", ", "]", -5) == "[, ... 3 more fields]")
-    assert(Utils.truncatedString(Seq(1, 2, 3), ", ") == "1, 2, 3")
-  }
-
   test("timeConversion") {
     // Test -1
     assert(Utils.timeStringAsSeconds("-1") === -1)

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala

@@ -25,9 +25,9 @@ import org.apache.spark.sql.catalyst.expressions.aggregate.DeclarativeAggregate
 import org.apache.spark.sql.catalyst.expressions.codegen._
 import org.apache.spark.sql.catalyst.expressions.codegen.Block._
 import org.apache.spark.sql.catalyst.trees.TreeNode
+import org.apache.spark.sql.catalyst.util.truncatedString
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.types._
-import org.apache.spark.util.Utils
 
 ////////////////////////////////////////////////////////////////////////////////////////////////////
 // This file defines the basic expression abstract classes in Catalyst.
@@ -237,7 +237,7 @@ abstract class Expression extends TreeNode[Expression] {
 
   override def simpleString: String = toString
 
-  override def toString: String = prettyName + Utils.truncatedString(
+  override def toString: String = prettyName + truncatedString(
     flatArguments.toSeq, "(", ", ", ")")
 
   /**

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala

@@ -24,8 +24,8 @@ import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.expressions.aggregate.AggregateExpression
 import org.apache.spark.sql.catalyst.plans._
 import org.apache.spark.sql.catalyst.plans.physical.{HashPartitioning, Partitioning, RangePartitioning, RoundRobinPartitioning}
+import org.apache.spark.sql.catalyst.util.truncatedString
 import org.apache.spark.sql.types._
-import org.apache.spark.util.Utils
 import org.apache.spark.util.random.RandomSampler
 
 /**
@@ -485,7 +485,7 @@ case class With(child: LogicalPlan, cteRelations: Seq[(String, SubqueryAlias)])
   override def output: Seq[Attribute] = child.output
 
   override def simpleString: String = {
-    val cteAliases = Utils.truncatedString(cteRelations.map(_._1), "[", ", ", "]")
+    val cteAliases = truncatedString(cteRelations.map(_._1), "[", ", ", "]")
     s"CTE $cteAliases"
   }
 

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreeNode.scala

@@ -37,9 +37,9 @@ import org.apache.spark.sql.catalyst.errors._
 import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.plans.JoinType
 import org.apache.spark.sql.catalyst.plans.physical.{BroadcastMode, Partitioning}
+import org.apache.spark.sql.catalyst.util.truncatedString
 import org.apache.spark.sql.types._
 import org.apache.spark.storage.StorageLevel
-import org.apache.spark.util.Utils
 
 /** Used by [[TreeNode.getNodeNumbered]] when traversing the tree for a given number */
 private class MutableInt(var i: Int)
@@ -440,10 +440,10 @@ abstract class TreeNode[BaseType <: TreeNode[BaseType]] extends Product {
     case tn: TreeNode[_] => tn.simpleString :: Nil
     case seq: Seq[Any] if seq.toSet.subsetOf(allChildren.asInstanceOf[Set[Any]]) => Nil
     case iter: Iterable[_] if iter.isEmpty => Nil
-    case seq: Seq[_] => Utils.truncatedString(seq, "[", ", ", "]") :: Nil
-    case set: Set[_] => Utils.truncatedString(set.toSeq, "{", ", ", "}") :: Nil
+    case seq: Seq[_] => truncatedString(seq, "[", ", ", "]") :: Nil
+    case set: Set[_] => truncatedString(set.toSeq, "{", ", ", "}") :: Nil
     case array: Array[_] if array.isEmpty => Nil
-    case array: Array[_] => Utils.truncatedString(array, "[", ", ", "]") :: Nil
+    case array: Array[_] => truncatedString(array, "[", ", ", "]") :: Nil
     case null => Nil
     case None => Nil
     case Some(null) => Nil
@@ -664,7 +664,7 @@ abstract class TreeNode[BaseType <: TreeNode[BaseType]] extends Product {
       t.forall(_.isInstanceOf[Partitioning]) || t.forall(_.isInstanceOf[DataType]) =>
       JArray(t.map(parseToJson).toList)
     case t: Seq[_] if t.length > 0 && t.head.isInstanceOf[String] =>
-      JString(Utils.truncatedString(t, "[", ", ", "]"))
+      JString(truncatedString(t, "[", ", ", "]"))
     case t: Seq[_] => JNull
     case m: Map[_, _] => JNull
     // if it's a scala object, we can simply keep the full class path.

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/package.scala

@@ -19,13 +19,16 @@ package org.apache.spark.sql.catalyst
 
 import java.io._
 import java.nio.charset.StandardCharsets
+import java.util.concurrent.atomic.AtomicBoolean
 
+import org.apache.spark.internal.Logging
 import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.types.{NumericType, StringType}
 import org.apache.spark.unsafe.types.UTF8String
 import org.apache.spark.util.Utils
 
-package object util {
+package object util extends Logging {
 
   /** Silences output to stderr or stdout for the duration of f */
   def quietly[A](f: => A): A = {
@@ -167,6 +170,38 @@ package object util {
     builder.toString()
   }
 
+  /** Whether we have warned about plan string truncation yet. */
+  private val truncationWarningPrinted = new AtomicBoolean(false)
+
+  /**
+   * Format a sequence with semantics similar to calling .mkString(). Any elements beyond
+   * maxNumToStringFields will be dropped and replaced by a "... N more fields" placeholder.
+   *
+   * @return the trimmed and formatted string.
+   */
+  def truncatedString[T](
+      seq: Seq[T],
+      start: String,
+      sep: String,
+      end: String,
+      maxNumFields: Int = SQLConf.get.maxToStringFields): String = {
+    if (seq.length > maxNumFields) {
+      if (truncationWarningPrinted.compareAndSet(false, true)) {
+        logWarning(
+          "Truncated the string representation of a plan since it was too large. This " +
+            s"behavior can be adjusted by setting '${SQLConf.MAX_TO_STRING_FIELDS.key}'.")
+      }
+      val numFields = math.max(0, maxNumFields - 1)
+      seq.take(numFields).mkString(
+        start, sep, sep + "... " + (seq.length - numFields) + " more fields" + end)
+    } else {
+      seq.mkString(start, sep, end)
+    }
+  }
+
+  /** Shorthand for calling truncatedString() without start or end strings. */
+  def truncatedString[T](seq: Seq[T], sep: String): String = truncatedString(seq, "", sep, "")
+
   /* FIX ME
   implicit class debugLogging(a: Any) {
     def debugLogging() {

sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala

@@ -1594,6 +1594,13 @@ object SQLConf {
         "WHERE, which does not follow SQL standard.")
       .booleanConf
       .createWithDefault(false)
+
+  val MAX_TO_STRING_FIELDS = buildConf("spark.sql.debug.maxToStringFields")
+    .doc("Maximum number of fields of sequence-like entries can be converted to strings " +
+      "in debug output. Any elements beyond the limit will be dropped and replaced by a" +
+      """ "... N more fields" placeholder.""")
+    .intConf
+    .createWithDefault(25)
 }
 
 /**
@@ -2009,6 +2016,8 @@ class SQLConf extends Serializable with Logging {
 
   def integralDivideReturnLong: Boolean = getConf(SQLConf.LEGACY_INTEGRALDIVIDE_RETURN_LONG)
 
+  def maxToStringFields: Int = getConf(SQLConf.MAX_TO_STRING_FIELDS)
+
   /** ********************** SQLConf functionality methods ************ */
 
   /** Set Spark SQL configuration properties. */

sql/catalyst/src/main/scala/org/apache/spark/sql/types/StructType.scala

@@ -27,7 +27,7 @@ import org.apache.spark.SparkException
 import org.apache.spark.annotation.Stable
 import org.apache.spark.sql.catalyst.expressions.{Attribute, AttributeReference, InterpretedOrdering}
 import org.apache.spark.sql.catalyst.parser.{CatalystSqlParser, LegacyTypeStringParser}
-import org.apache.spark.sql.catalyst.util.quoteIdentifier
+import org.apache.spark.sql.catalyst.util.{quoteIdentifier, truncatedString}
 import org.apache.spark.util.Utils
 
 /**
@@ -346,7 +346,7 @@ case class StructType(fields: Array[StructField]) extends DataType with Seq[Stru
 
   override def simpleString: String = {
     val fieldTypes = fields.view.map(field => s"${field.name}:${field.dataType.simpleString}")
-    Utils.truncatedString(fieldTypes, "struct<", ",", ">")
+    truncatedString(fieldTypes, "struct<", ",", ">")
   }
 
   override def catalogString: String = {

sql/catalyst/src/test/scala/org/apache/spark/sql/util/UtilSuite.scala

@@ -0,0 +1,31 @@
+/*
+ * 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.util
+
+import org.apache.spark.SparkFunSuite
+import org.apache.spark.sql.catalyst.util.truncatedString
+
+class UtilSuite extends SparkFunSuite {
+  test("truncatedString") {
+    assert(truncatedString(Nil, "[", ", ", "]", 2) == "[]")
+    assert(truncatedString(Seq(1, 2), "[", ", ", "]", 2) == "[1, 2]")
+    assert(truncatedString(Seq(1, 2, 3), "[", ", ", "]", 2) == "[1, ... 2 more fields]")
+    assert(truncatedString(Seq(1, 2, 3), "[", ", ", "]", -5) == "[, ... 3 more fields]")
+    assert(truncatedString(Seq(1, 2, 3), ", ") == "1, 2, 3")
+  }
+}

sql/core/src/main/scala/org/apache/spark/sql/execution/DataSourceScanExec.scala

@@ -30,6 +30,7 @@ import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.expressions.codegen.CodegenContext
 import org.apache.spark.sql.catalyst.plans.QueryPlan
 import org.apache.spark.sql.catalyst.plans.physical.{HashPartitioning, Partitioning, UnknownPartitioning}
+import org.apache.spark.sql.catalyst.util.truncatedString
 import org.apache.spark.sql.execution.datasources._
 import org.apache.spark.sql.execution.datasources.parquet.{ParquetFileFormat => ParquetSource}
 import org.apache.spark.sql.execution.metric.SQLMetrics
@@ -56,8 +57,8 @@ trait DataSourceScanExec extends LeafExecNode with CodegenSupport {
       case (key, value) =>
         key + ": " + StringUtils.abbreviate(redact(value), 100)
     }
-    val metadataStr = Utils.truncatedString(metadataEntries, " ", ", ", "")
-    s"$nodeNamePrefix$nodeName${Utils.truncatedString(output, "[", ",", "]")}$metadataStr"
+    val metadataStr = truncatedString(metadataEntries, " ", ", ", "")
+    s"$nodeNamePrefix$nodeName${truncatedString(output, "[", ",", "]")}$metadataStr"
   }
 
   override def verboseString: String = redact(super.verboseString)

sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala

@@ -24,9 +24,9 @@ import org.apache.spark.sql.catalyst.analysis.MultiInstanceRelation
 import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.plans.logical._
 import org.apache.spark.sql.catalyst.plans.physical.{Partitioning, UnknownPartitioning}
+import org.apache.spark.sql.catalyst.util.truncatedString
 import org.apache.spark.sql.execution.metric.SQLMetrics
 import org.apache.spark.sql.types.DataType
-import org.apache.spark.util.Utils
 
 object RDDConversions {
   def productToRowRdd[A <: Product](data: RDD[A], outputTypes: Seq[DataType]): RDD[InternalRow] = {
@@ -197,6 +197,6 @@ case class RDDScanExec(
   }
 
   override def simpleString: String = {
-    s"$nodeName${Utils.truncatedString(output, "[", ",", "]")}"
+    s"$nodeName${truncatedString(output, "[", ",", "]")}"
   }
 }

sql/core/src/main/scala/org/apache/spark/sql/execution/QueryExecution.scala

@@ -31,6 +31,7 @@ import org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker
 import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, ReturnAnswer}
 import org.apache.spark.sql.catalyst.rules.Rule
 import org.apache.spark.sql.catalyst.util.DateTimeUtils
+import org.apache.spark.sql.catalyst.util.truncatedString
 import org.apache.spark.sql.execution.command.{DescribeTableCommand, ExecutedCommandExec, ShowTablesCommand}
 import org.apache.spark.sql.execution.exchange.{EnsureRequirements, ReuseExchange}
 import org.apache.spark.sql.types.{BinaryType, DateType, DecimalType, TimestampType, _}
@@ -206,7 +207,7 @@ class QueryExecution(val sparkSession: SparkSession, val logical: LogicalPlan) {
     writer.write("== Parsed Logical Plan ==\n")
     writeOrError(writer)(logical.treeString(_, verbose, addSuffix))
     writer.write("\n== Analyzed Logical Plan ==\n")
-    val analyzedOutput = stringOrError(Utils.truncatedString(
+    val analyzedOutput = stringOrError(truncatedString(
       analyzed.output.map(o => s"${o.name}: ${o.dataType.simpleString}"), ", "))
     writer.write(analyzedOutput)
     writer.write("\n")

sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/HashAggregateExec.scala

@@ -27,6 +27,7 @@ import org.apache.spark.sql.catalyst.expressions.aggregate._
 import org.apache.spark.sql.catalyst.expressions.codegen._
 import org.apache.spark.sql.catalyst.expressions.codegen.Block._
 import org.apache.spark.sql.catalyst.plans.physical._
+import org.apache.spark.sql.catalyst.util.truncatedString
 import org.apache.spark.sql.execution._
 import org.apache.spark.sql.execution.metric.{SQLMetric, SQLMetrics}
 import org.apache.spark.sql.execution.vectorized.MutableColumnarRow
@@ -930,9 +931,9 @@ case class HashAggregateExec(
 
     testFallbackStartsAt match {
       case None =>
-        val keyString = Utils.truncatedString(groupingExpressions, "[", ", ", "]")
-        val functionString = Utils.truncatedString(allAggregateExpressions, "[", ", ", "]")
-        val outputString = Utils.truncatedString(output, "[", ", ", "]")
+        val keyString = truncatedString(groupingExpressions, "[", ", ", "]")
+        val functionString = truncatedString(allAggregateExpressions, "[", ", ", "]")
+        val outputString = truncatedString(output, "[", ", ", "]")
         if (verbose) {
           s"HashAggregate(keys=$keyString, functions=$functionString, output=$outputString)"
         } else {

sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/ObjectHashAggregateExec.scala

@@ -23,9 +23,9 @@ import org.apache.spark.sql.catalyst.errors._
 import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.catalyst.expressions.aggregate._
 import org.apache.spark.sql.catalyst.plans.physical._
+import org.apache.spark.sql.catalyst.util.truncatedString
 import org.apache.spark.sql.execution._
 import org.apache.spark.sql.execution.metric.SQLMetrics
-import org.apache.spark.util.Utils
 
 /**
  * A hash-based aggregate operator that supports [[TypedImperativeAggregate]] functions that may
@@ -143,9 +143,9 @@ case class ObjectHashAggregateExec(
 
   private def toString(verbose: Boolean): String = {
     val allAggregateExpressions = aggregateExpressions
-    val keyString = Utils.truncatedString(groupingExpressions, "[", ", ", "]")
-    val functionString = Utils.truncatedString(allAggregateExpressions, "[", ", ", "]")
-    val outputString = Utils.truncatedString(output, "[", ", ", "]")
+    val keyString = truncatedString(groupingExpressions, "[", ", ", "]")
+    val functionString = truncatedString(allAggregateExpressions, "[", ", ", "]")
+    val outputString = truncatedString(output, "[", ", ", "]")
     if (verbose) {
       s"ObjectHashAggregate(keys=$keyString, functions=$functionString, output=$outputString)"
     } else {