Qualification tool: Report write data format and nested types

docs/additional-functionality/qualification-profiling-tools.md

@@ -60,7 +60,7 @@ Here are 2 options:
 ```bash
 git clone https://github.com/NVIDIA/spark-rapids.git
 cd spark-rapids
-mvn -pl .,tools clean verify -DskipTests
+mvn -Pdefault -pl .,tools clean verify -DskipTests
 ```
 The jar is generated in below directory :
 
@@ -144,14 +144,20 @@ you are running on needs to be taken into account.
 had to estimate it, it means the event log was missing the application finished event so we will use the last job
 or sql execution time we find as the end time used to calculate the duration.
 
+`Complex Types and Unsupported Nested Complex Types` looks at the Read Schema and reports if there are any complex types(array, struct or maps)
+in the schema. Nested complex types are complex types which contain other complex types (Example: array<struct<string,string>>).
+Note that it can read all the schemas for DataSource V1. The Data Source V2 truncates the schema, so if you see ...,
+then the full schema is not available. For such schemas we read until ... and report if there are any complex types and
+nested complex types in that.
+
 Note that SQL queries that contain failed jobs are not included.
 
 Sample output in csv:
 
 ```
-App Name,App ID,Score,Potential Problems,SQL DF Duration,SQL Dataframe Task Duration,App Duration,Executor CPU Time Percent,App Duration Estimated,SQL Duration with Potential Problems,SQL Ids with Failures,Read Score Percent,Read File Format Score,Unsupported Read File Formats and Types
-job3,app-20210507174503-1704,4320658.0,"",9569,4320658,26171,35.34,false,0,"",20,100.0,""
-job1,app-20210507174503-2538,19864.04,"",6760,21802,83728,71.3,false,0,"",20,55.56,"Parquet[decimal]"
+App Name,App ID,Score,Potential Problems,SQL DF Duration,SQL Dataframe Task Duration,App Duration,Executor CPU Time Percent,App Duration Estimated,SQL Duration with Potential Problems,SQL Ids with Failures,Read Score Percent,Read File Format Score,Unsupported Read File Formats and Types,Unsupported Write Data Format,Complex Types,Unsupported Nested Complex Types
+job3,app-20210507174503-1704,4320658.0,"",9569,4320658,26171,35.34,false,0,"",20,100.0,"",JSON,array<struct<city:string;state:string>>;map<string;string>,array<struct<city:string;state:string>>
+job1,app-20210507174503-2538,19864.04,"",6760,21802,83728,71.3,false,0,"",20,55.56,"Parquet[decimal]",JSON;CSV,"",""
 ```
 
 Sample output in text:

sql-plugin/src/main/scala/com/nvidia/spark/rapids/TypeChecks.scala

@@ -2019,10 +2019,12 @@ object SupportedOpsForTools {
     val conf = new RapidsConf(Map.empty[String, String])
     val types = TypeEnum.values.toSeq
     val header = Seq("Format", "Direction") ++ types
+    val writeOps: Array[String] = Array.fill(types.size)("NA")
     println(header.mkString(","))
     GpuOverrides.fileFormats.toSeq.sortBy(_._1.toString).foreach {
       case (format, ioMap) =>
-        val formatEnabled = format.toString.toLowerCase match {
+        val formatLowerCase = format.toString.toLowerCase
+        val formatEnabled = formatLowerCase match {
           case "csv" => conf.isCsvEnabled && conf.isCsvReadEnabled
           case "parquet" => conf.isParquetEnabled && conf.isParquetReadEnabled
           case "orc" => conf.isOrcEnabled && conf.isOrcReadEnabled
@@ -2059,8 +2061,13 @@ object SupportedOpsForTools {
             read.support(t).text
           }
         }
-        // only support reads for now
+        // print read formats and types
         println(s"${(Seq(format, "read") ++ readOps).mkString(",")}")
+
+        // print write formats and NA for types. Cannot determine types from event logs.
+        if (!formatLowerCase.equals("csv")) {
+          println(s"${(Seq(format, "write") ++ writeOps).mkString(",")}")
+        }
     }
   }
 

tools/src/main/resources/supportedDataSource.csv

@@ -1,4 +1,6 @@
 Format,Direction,BOOLEAN,BYTE,SHORT,INT,LONG,FLOAT,DOUBLE,DATE,TIMESTAMP,STRING,DECIMAL,NULL,BINARY,CALENDAR,ARRAY,MAP,STRUCT,UDT
 CSV,read,CO,CO,CO,CO,CO,CO,CO,CO,CO,S,CO,NA,NS,NA,NA,NA,NA,NA
 ORC,read,S,S,S,S,S,S,S,S,PS,S,CO,NA,NS,NA,PS,NS,PS,NS
+ORC,write,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
 Parquet,read,S,S,S,S,S,S,S,S,PS,S,CO,NA,NS,NA,PS,PS,PS,NS
+Parquet,write,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA

tools/src/main/scala/com/nvidia/spark/rapids/tool/qualification/PluginTypeChecker.scala

@@ -16,7 +16,7 @@
 
 package com.nvidia.spark.rapids.tool.qualification
 
-import scala.collection.mutable.HashMap
+import scala.collection.mutable.{ArrayBuffer,HashMap}
 import scala.io.{BufferedSource, Source}
 
 /**
@@ -38,28 +38,35 @@ class PluginTypeChecker {
   private val DEFAULT_DS_FILE = "supportedDataSource.csv"
 
   // map of file format => Map[support category => Seq[Datatypes for that category]]
-  // contains the details of formats to which ones have datatypes not supported
-  // var for testing puposes
-  private var formatsToSupportedCategory = readSupportedTypesForPlugin
+  // contains the details of formats to which ones have datatypes not supported.
+  // Write formats contains only the formats that are supported. Types cannot be determined
+  // from event logs for write formats.
+  // var for testing purposes
+  private var (readFormatsAndTypes, writeFormats) = readSupportedTypesForPlugin
 
   // for testing purposes only
   def setPluginDataSourceFile(filePath: String): Unit = {
     val source = Source.fromFile(filePath)
-    formatsToSupportedCategory = readSupportedTypesForPlugin(source)
+    val (readFormatsAndTypesTest, writeFormatsTest) = readSupportedTypesForPlugin(source)
+    readFormatsAndTypes = readFormatsAndTypesTest
+    writeFormats = writeFormatsTest
   }
 
-  private def readSupportedTypesForPlugin: Map[String, Map[String, Seq[String]]] = {
+  private def readSupportedTypesForPlugin: (
+      Map[String, Map[String, Seq[String]]], ArrayBuffer[String]) = {
     val source = Source.fromResource(DEFAULT_DS_FILE)
     readSupportedTypesForPlugin(source)
   }
 
   // file format should be like this:
   // Format,Direction,BOOLEAN,BYTE,SHORT,INT,LONG,FLOAT,DOUBLE,DATE,...
   // CSV,read,S,S,S,S,S,S,S,S,S*,S,NS,NA,NS,NA,NA,NA,NA,NA
+  // Parquet,write,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA,NA
   private def readSupportedTypesForPlugin(
-      source: BufferedSource): Map[String, Map[String, Seq[String]]] = {
+      source: BufferedSource): (Map[String, Map[String, Seq[String]]], ArrayBuffer[String]) = {
     // get the types the Rapids Plugin supports
     val allSupportedReadSources = HashMap.empty[String, Map[String, Seq[String]]]
+    val allSupportedWriteFormats = ArrayBuffer[String]()
     try {
       val fileContents = source.getLines().toSeq
       if (fileContents.size < 2) {
@@ -85,12 +92,14 @@ class PluginTypeChecker {
           val allNsTypes = nsTypes.flatMap(t => getOtherTypes(t) :+ t)
           val allBySup = HashMap(NS -> allNsTypes)
           allSupportedReadSources.put(format, allBySup.toMap)
+        } else if (direction.equals("write")) {
+          allSupportedWriteFormats += format
         }
       }
     } finally {
       source.close()
     }
-    allSupportedReadSources.toMap
+    (allSupportedReadSources.toMap, allSupportedWriteFormats)
   }
 
   def getOtherTypes(typeRead: String): Seq[String] = {
@@ -114,7 +123,7 @@ class PluginTypeChecker {
   def scoreReadDataTypes(format: String, schema: String): (Double, Set[String]) = {
     val schemaLower = schema.toLowerCase
     val formatInLower = format.toLowerCase
-    val typesBySup = formatsToSupportedCategory.get(formatInLower)
+    val typesBySup = readFormatsAndTypes.get(formatInLower)
     val score = typesBySup match {
       case Some(dtSupMap) =>
         // check if any of the not supported types are in the schema
@@ -140,4 +149,9 @@ class PluginTypeChecker {
     }
     score
   }
+
+  def isWriteFormatsupported(writeFormat: ArrayBuffer[String]): ArrayBuffer[String] = {
+    writeFormat.map(x => x.toLowerCase.trim).filterNot(
+      writeFormats.map(x => x.trim).contains(_))
+  }
 }

tools/src/main/scala/com/nvidia/spark/rapids/tool/qualification/QualOutputWriter.scala

@@ -44,7 +44,8 @@ class QualOutputWriter(outputDir: String, reportReadSchema: Boolean, printStdout
     val initHeader = s"App Name,$appIdStr,Score,Potential Problems,$sqlDurStr,$taskDurStr," +
       s"$appDurStr,Executor CPU Time Percent,App Duration Estimated," +
       "SQL Duration with Potential Problems,SQL Ids with Failures,Read Score Percent," +
-      "Read File Format Score,Unsupported Read File Formats and Types"
+      "Read File Format Score,Unsupported Read File Formats and Types," +
+      "Unsupported Write Data Format,Unsupported Nested Types"
     if (reportReadSchema) {
       initHeader + ",Read Schema"
     } else {
@@ -73,16 +74,19 @@ class QualOutputWriter(outputDir: String, reportReadSchema: Boolean, printStdout
     val failedIds = stringIfempty(appSum.failedSQLIds)
     // since csv, replace any commas with ; in the schema
     val readFileFormats = stringIfempty(appSum.readFileFormats.replace(",", ";"))
+    val complexTypes = stringIfempty(appSum.complexTypes.replace(",", ";"))
+    val nestedComplexTypes = stringIfempty(appSum.nestedComplexTypes.replace(",", ";"))
     val readFileScoreRounded = f"${appSum.readFileFormatScore}%1.2f"
     val readFormatNS = stringIfempty(appSum.readFileFormatAndTypesNotSupported)
+    val writeDataFormat = stringIfempty(appSum.writeDataFormat)
 
 
     val initRow = s"$appNameStr,$appIdStr,${appSum.score},$probStr," +
       s"${appSum.sqlDataFrameDuration},${appSum.sqlDataframeTaskDuration}," +
       s"${appSum.appDuration},${appSum.executorCpuTimePercent}," +
       s"${appSum.endDurationEstimated},${appSum.sqlDurationForProblematic},$failedIds," +
       s"${appSum.readScorePercent},${appSum.readFileFormatScore}," +
-      s"${readFormatNS}"
+      s"${readFormatNS},${writeDataFormat},${complexTypes},${nestedComplexTypes}"
     if (reportReadSchema) {
       initRow + s",$readFileFormats"
     } else {

tools/src/main/scala/org/apache/spark/sql/rapids/tool/qualification/QualAppInfo.scala

@@ -41,6 +41,7 @@ class QualAppInfo(
   var isPluginEnabled = false
   var lastJobEndTime: Option[Long] = None
   var lastSQLEndTime: Option[Long] = None
+  val writeDataFormat: ArrayBuffer[String] = ArrayBuffer[String]()
 
   var appInfo: Option[QualApplicationInfo] = None
   val sqlStart: HashMap[Long, QualSQLExecutionInfo] = HashMap[Long, QualSQLExecutionInfo]()
@@ -184,6 +185,91 @@ class QualAppInfo(
     }.getOrElse(1.0)
   }
 
+  def reportComplexTypes: (String, String) = {
+    if (dataSourceInfo.size != 0) {
+      val schema = dataSourceInfo.map { ds => ds.schema }
+      parseReadSchemaForNestedTypes(schema)
+    } else {
+      ("", "")
+    }
+  }
+
+  private def parseReadSchemaForNestedTypes(schema: ArrayBuffer[String]): (String, String) = {
+    val tempStringBuilder = new StringBuilder()
+    val individualSchema: ArrayBuffer[String] = new ArrayBuffer()
+    var angleBracketsCount = 0
+    var parenthesesCount = 0
+    val distinctSchema = schema.distinct.mkString(",")
+
+    // Get the nested types i.e everything between < >
+    for (char <- distinctSchema) {
+      char match {
+        case '<' => angleBracketsCount += 1
+        case '>' => angleBracketsCount -= 1
+        // If the schema has decimals, Example decimal(6,2) then we have to make sure it has both
+        // opening and closing parentheses(unless the string is incomplete due to V2 reader).
+        case '(' => parenthesesCount += 1
+        case ')' => parenthesesCount -= 1
+        case _ =>
+      }
+      if (angleBracketsCount == 0 && parenthesesCount == 0 && char.equals(',')) {
+        individualSchema += tempStringBuilder.toString
+        tempStringBuilder.setLength(0)
+      }
+      else {
+        tempStringBuilder.append(char);
+      }
+    }
+    if (!tempStringBuilder.isEmpty) {
+      individualSchema += tempStringBuilder.toString
+    }
+
+    // If DataSource V2 is used, then Schema may be incomplete with ... appended at the end.
+    // We determine complex types and nested complex types until ...
+    val incompleteSchema = individualSchema.filter(x => x.contains("..."))
+    val completeSchema = individualSchema.filterNot(x => x.contains("..."))
+
+    // Check if it has types
+    val incompleteTypes = incompleteSchema.map { x =>
+      if (x.contains("...") && x.contains(":")) {
+        x.split(":", 2)(1).split("\\.\\.\\.")(0)
+      } else {
+        ""
+      }
+    }
+    // Omit columnName and get only schemas
+    val completeTypes = completeSchema.map(x => x.split(":", 2)(1))
+    val schemaTypes = completeTypes ++ incompleteTypes
+
+    // Filter only complex types.
+    // Example: array<string>, array<struct<string, string>>
+    val complexTypes = schemaTypes.filter(x =>
+      x.startsWith("array<") || x.startsWith("map<") || x.startsWith("struct<"))
+
+    // Determine nested complex types from complex types
+    // Example: array<struct<string, string>> is nested complex type.
+    val nestedComplexTypes = complexTypes.filter(complexType => {
+      val startIndex = complexType.indexOf('<')
+      val closedBracket = complexType.lastIndexOf('>')
+      // If String is incomplete due to dsv2, then '>' may not be present. In that case traverse
+      // until length of the incomplete string
+      val lastIndex = if (closedBracket == -1) {
+        complexType.length - 1
+      } else {
+        closedBracket
+      }
+      val string = complexType.substring(startIndex, lastIndex + 1)
+      string.contains("array<") || string.contains("struct<") || string.contains("map<")
+    })
+
+    // Since it is saved as csv, replace commas with ;
+    val complexTypesResult = complexTypes.filter(_.nonEmpty).mkString(";").replace(",", ";")
+    val nestedComplexTypesResult = nestedComplexTypes.filter(
+      _.nonEmpty).mkString(";").replace(",", ";")
+
+    (complexTypesResult, nestedComplexTypesResult)
+  }
+
   def aggregateStats(): Option[QualificationSummaryInfo] = {
     appInfo.map { info =>
       val appDuration = calculateAppDuration(info.startTime).getOrElse(0L)
@@ -205,12 +291,14 @@ class QualAppInfo(
         val typeString = types.mkString(":").replace(",", ":")
         s"${format}[$typeString]"
       }.mkString(";")
+      val writeFormat = writeFormatNotSupported(writeDataFormat)
+      val (allComplexTypes, nestedComplexTypes) = reportComplexTypes
 
       new QualificationSummaryInfo(info.appName, appId, scoreRounded, problems,
         sqlDataframeDur, sqlDataframeTaskDuration, appDuration, executorCpuTimePercent,
         endDurationEstimated, sqlDurProblem, failedIds, readScorePercent,
         readScoreHumanPercentRounded, notSupportFormatAndTypesString,
-        getAllReadFileFormats)
+        getAllReadFileFormats, writeFormat, allComplexTypes, nestedComplexTypes)
     }
   }
 
@@ -228,8 +316,22 @@ class QualAppInfo(
         val existingIssues = sqlIDtoProblematic.getOrElse(sqlID, Set.empty[String])
         sqlIDtoProblematic(sqlID) = existingIssues ++ issues
       }
+      // Get the write data format
+      if (node.name.contains("InsertIntoHadoopFsRelationCommand")) {
+        val writeFormat = node.desc.split(",")(2)
+        writeDataFormat += writeFormat
+      }
     }
   }
+
+  def writeFormatNotSupported(writeFormat: ArrayBuffer[String]): String = {
+    // Filter unsupported write data format
+    val unSupportedWriteFormat = pluginTypeChecker.map { checker =>
+      checker.isWriteFormatsupported(writeFormat)
+    }.getOrElse(ArrayBuffer[String]())
+
+    unSupportedWriteFormat.distinct.mkString(";").toUpperCase
+  }
 }
 
 class StageTaskQualificationSummary(
@@ -273,7 +375,10 @@ case class QualificationSummaryInfo(
     readScorePercent: Int,
     readFileFormatScore: Double,
     readFileFormatAndTypesNotSupported: String,
-    readFileFormats: String)
+    readFileFormats: String,
+    writeDataFormat: String,
+    complexTypes: String,
+    nestedComplexTypes: String)
 
 object QualAppInfo extends Logging {
   def createApp(

tools/src/test/resources/QualificationExpectations/complex_dec_expectation.csv

@@ -1,2 +1,2 @@
-App Name,App ID,Score,Potential Problems,SQL DF Duration,SQL Dataframe Task Duration,App Duration,Executor CPU Time Percent,App Duration Estimated,SQL Duration with Potential Problems,SQL Ids with Failures,Read Score Percent,Read File Format Score,Unsupported Read File Formats and Types
-Spark shell,local-1626104300434,1322.1,DECIMAL,2429,1469,131104,88.35,false,160,"",20,50.0,Parquet[decimal];ORC[map:decimal]
+App Name,App ID,Score,Potential Problems,SQL DF Duration,SQL Dataframe Task Duration,App Duration,Executor CPU Time Percent,App Duration Estimated,SQL Duration with Potential Problems,SQL Ids with Failures,Read Score Percent,Read File Format Score,Unsupported Read File Formats and Types,Unsupported Write Data Format,Complex Types,Unsupported Nested Complex Types
+Spark shell,local-1626104300434,1322.1,DECIMAL,2429,1469,131104,88.35,false,160,"",20,50.0,Parquet[decimal];ORC[map:decimal],"",struct<firstname:string;middlename:array<string>;lastname:string>;struct<current:struct<state:string;city:string>;previous:struct<state:map<string;string>;city:string>>;array<struct<city:string;state:string>>;map<string;string>;map<string;array<string>>;map<string;map<string;string>>;array<array<string>>;array<string>,struct<firstname:string;middlename:array<string>;lastname:string>;struct<current:struct<state:string;city:string>;previous:struct<state:map<string;string>;city:string>>;array<struct<city:string;state:string>>;map<string;array<string>>;map<string;map<string;string>>;array<array<string>>

tools/src/test/resources/QualificationExpectations/db_sim_test_expectation.csv

@@ -1,2 +1,2 @@
-App Name,App ID,Score,Potential Problems,SQL Dataframe Duration,SQL Dataframe Task Duration,App Duration,Executor CPU Time Percent,App Duration Estimated,SQL Duration with Potential Problems,SQL Ids with Failures,Read Score Percent,ReadFileFormat Score,Unsupported Read File Formats and Types
-Spark shell,local-1623876083964,1417661.00,"",119903,1417661,133857,91.14,false,0,"",20,100.00,""
+App Name,App ID,Score,Potential Problems,SQL Dataframe Duration,SQL Dataframe Task Duration,App Duration,Executor CPU Time Percent,App Duration Estimated,SQL Duration with Potential Problems,SQL Ids with Failures,Read Score Percent,ReadFileFormat Score,Unsupported Read File Formats and Types,Unsupported Write Data Format,Complex Types,Unsupported Nested Complex Types
+Spark shell,local-1623876083964,1417661.00,"",119903,1417661,133857,91.14,false,0,"",20,100.00,"","","",""

tools/src/test/resources/QualificationExpectations/decimal_part_expectation.csv

@@ -1,2 +1,2 @@
-App Name,App ID,Score,Potential Problems,SQL DF Duration,SQL Dataframe Task Duration,App Duration,Executor CPU Time Percent,App Duration Estimated,SQL Duration with Potential Problems,SQL Ids with Failures,Read Score Percent,Read File Format Score,Unsupported Read File Formats and Types
-Spark shell,local-1626189209260,1052.3,DECIMAL,1314,1238,106033,57.21,false,1023,"",20,25.0,Parquet[decimal]
+App Name,App ID,Score,Potential Problems,SQL DF Duration,SQL Dataframe Task Duration,App Duration,Executor CPU Time Percent,App Duration Estimated,SQL Duration with Potential Problems,SQL Ids with Failures,Read Score Percent,Read File Format Score,Unsupported Read File Formats and Types,Unsupported Write Data Format,Complex Types,Unsupported Nested Complex Types
+Spark shell,local-1626189209260,1052.3,DECIMAL,1314,1238,106033,57.21,false,1023,"",20,25.0,Parquet[decimal],"",array<struct<city:string;state:string>>;map<string;string>;map<string;array<string>>;map<string;map<string;string>>,array<struct<city:string;state:string>>;map<string;array<string>>;map<string;map<string;string>>

tools/src/test/resources/QualificationExpectations/directory_test_expectation.csv

@@ -1,2 +1,2 @@
-App Name,App ID,Score,Potential Problems,SQL Dataframe Duration,SQL Dataframe Task Duration,App Duration,Executor CPU Time Percent,App Duration Estimated,SQL Duration with Potential Problems,SQL Ids with Failures,Read Score Percent,ReadFileFormat Score,Unsupported Read File Formats and Types
-Spark shell,local-1623876083964,1417661.00,"",119903,1417661,133857,91.14,false,0,"",20,100.00,""
+App Name,App ID,Score,Potential Problems,SQL Dataframe Duration,SQL Dataframe Task Duration,App Duration,Executor CPU Time Percent,App Duration Estimated,SQL Duration with Potential Problems,SQL Ids with Failures,Read Score Percent,ReadFileFormat Score,Unsupported Read File Formats and Types,Unsupported Write Data Format,Complex Types,Unsupported Nested Complex Types
+Spark shell,local-1623876083964,1417661.00,"",119903,1417661,133857,91.14,false,0,"",20,100.00,"","","",""