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[KYLIN-5401]Optimize code logic for pushdown queries #2077

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Original file line number Diff line number Diff line change
Expand Up @@ -26,9 +26,7 @@ import org.apache.kylin.common.{KylinConfig, QueryContextFacade}
import org.apache.kylin.engine.spark.metadata.cube.StructField
import org.apache.kylin.query.runtime.plans.QueryToExecutionIDCache
import org.apache.spark.network.util.JavaUtils
import org.apache.spark.sql.functions._
import org.apache.spark.sql.hive.utils.{QueryMetricUtils, ResourceDetectUtils}
import org.apache.spark.sql.types.StringType
import org.apache.spark.sql.utils.SparkTypeUtil
import org.apache.spark.sql.{DataFrame, SparkSession}
import org.slf4j.{Logger, LoggerFactory}
Expand Down Expand Up @@ -75,15 +73,9 @@ object SparkSqlClient {
ss.sparkContext.setJobGroup(jobGroup,
"Pushdown Query Id: " + QueryContextFacade.current().getQueryId, interruptOnCancel = true)
try {
val temporarySchema = df.schema.fields.zipWithIndex.map {
case (_, index) => s"temporary_$index"
}
val tempDF = df.toDF(temporarySchema: _*)
val columns = tempDF.schema.map(tp => col(s"`${tp.name}`").cast(StringType))
val frame = tempDF.select(columns: _*)
val rowList = frame.collect().map(_.toSeq.map(_.asInstanceOf[String]).asJava).toSeq.asJava
val rowList = df.collect().map(_.toSeq.map(col => if (col == null) "" else col.toString).asJava).toSeq.asJava
val fieldList = df.schema.map(field => SparkTypeUtil.convertSparkFieldToJavaField(field)).asJava
val (scanRows, scanFiles, metadataTime, scanTime, scanBytes) = QueryMetricUtils.collectScanMetrics(frame.queryExecution.executedPlan)
val (scanRows, scanFiles, metadataTime, scanTime, scanBytes) = QueryMetricUtils.collectScanMetrics(df.queryExecution.executedPlan)
QueryContextFacade.current().addAndGetScannedRows(scanRows.asScala.map(Long2long(_)).sum)
QueryContextFacade.current().addAndGetScanFiles(scanFiles.asScala.map(Long2long(_)).sum)
QueryContextFacade.current().addAndGetScannedBytes(scanBytes.asScala.map(Long2long(_)).sum)
Expand Down