reformat code using sbt scalafmtAll (opensearch-project#67)

* reformat code using `sbt scalafmtAll` Signed-off-by: Kaituo Li <[email protected]> * added style check in CI Signed-off-by: Kaituo Li <[email protected]> --------- Signed-off-by: Kaituo Li <[email protected]>
YANG-DB · Oct 10, 2023 · 15d7911 · 15d7911
1 parent 6e7c88a
commit 15d7911
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Showing 8 changed files with 119 additions and 161 deletions.
diff --git a/.github/workflows/test-and-build-workflow.yml b/.github/workflows/test-and-build-workflow.yml
@@ -24,3 +24,6 @@ jobs:
 
       - name: Integ Test
         run: sbt integtest/test
+
+      - name: Style check
+        run: sbt scalafmtCheckAll
diff --git a/...spark-integration/src/main/scala/org/opensearch/flint/spark/sql/FlintSparkSqlParser.scala b/...spark-integration/src/main/scala/org/opensearch/flint/spark/sql/FlintSparkSqlParser.scala
@@ -79,7 +79,6 @@ class FlintSparkSqlParser(sparkParser: ParserInterface) extends ParserInterface
 
   override def parseQuery(sqlText: String): LogicalPlan = sparkParser.parseQuery(sqlText)
 
-
   // Starting from here is copied and modified from Spark 3.3.1
 
   protected def parse[T](sqlText: String)(toResult: FlintSparkSqlExtensionsParser => T): T = {

diff --git a/...-spark-integration/src/main/scala/org/opensearch/flint/spark/sql/SparkSqlAstBuilder.scala b/...-spark-integration/src/main/scala/org/opensearch/flint/spark/sql/SparkSqlAstBuilder.scala
@@ -15,8 +15,8 @@ import org.opensearch.flint.spark.sql.FlintSparkSqlExtensionsParser.{PropertyKey
 import org.apache.spark.sql.catalyst.parser.ParserUtils.string
 
 /**
- * AST builder that builds for common rule in Spark SQL grammar. The main logic is modified slightly
- * from Spark AstBuilder code.
+ * AST builder that builds for common rule in Spark SQL grammar. The main logic is modified
+ * slightly from Spark AstBuilder code.
  */
 trait SparkSqlAstBuilder extends FlintSparkSqlExtensionsVisitor[AnyRef] {
 

diff --git a/...k-integration/src/test/scala/org/apache/spark/sql/flint/datatype/FlintDataTypeSuite.scala b/...k-integration/src/test/scala/org/apache/spark/sql/flint/datatype/FlintDataTypeSuite.scala
@@ -163,7 +163,7 @@ class FlintDataTypeSuite extends FlintSuite with Matchers {
       StructField("varcharTextField", VarcharType(20), true, textMetadata) ::
         StructField("charTextField", CharType(20), true, textMetadata) ::
         Nil)
-      FlintDataType.serialize(sparkStructType) shouldBe compactJson(flintDataType)
+    FlintDataType.serialize(sparkStructType) shouldBe compactJson(flintDataType)
     // flint data type should not deserialize to varchar or char
     FlintDataType.deserialize(flintDataType) should contain theSameElementsAs StructType(
       StructField("varcharTextField", StringType, true, textMetadata) ::

diff --git a/spark-sql-application/src/main/scala/org/apache/spark/sql/FlintJob.scala b/spark-sql-application/src/main/scala/org/apache/spark/sql/FlintJob.scala
@@ -8,12 +8,13 @@ package org.apache.spark.sql
 
 import java.util.Locale
 
+import scala.concurrent.{ExecutionContext, Future, TimeoutException}
+import scala.concurrent.duration.{Duration, MINUTES}
+
 import org.opensearch.ExceptionsHelper
 import org.opensearch.flint.core.{FlintClient, FlintClientBuilder}
 import org.opensearch.flint.core.metadata.FlintMetadata
 import play.api.libs.json._
-import scala.concurrent.{ExecutionContext, Future, TimeoutException}
-import scala.concurrent.duration.{Duration, MINUTES}
 
 import org.apache.spark.SparkConf
 import org.apache.spark.internal.Logging
@@ -23,14 +24,14 @@ import org.apache.spark.util.ThreadUtils
 
 /**
  * Spark SQL Application entrypoint
-  *
-  * @param args
-  *   (0) sql query
-  * @param args
-  *   (1) opensearch index name
-  * @return
-  *   write sql query result to given opensearch index
-  */
+ *
+ * @param args
+ *   (0) sql query
+ * @param args
+ *   (1) opensearch index name
+ * @return
+ *   write sql query result to given opensearch index
+ */
 object FlintJob extends Logging {
   def main(args: Array[String]): Unit = {
     // Validate command line arguments
@@ -48,7 +49,7 @@ object FlintJob extends Logging {
     val threadPool = ThreadUtils.newDaemonFixedThreadPool(1, "check-create-index")
     implicit val executionContext = ExecutionContext.fromExecutor(threadPool)
 
-    var dataToWrite : Option[DataFrame] = None
+    var dataToWrite: Option[DataFrame] = None
     try {
       // flintClient needs spark session to be created first. Otherwise, we will have connection
       // exception from EMR-S to OS.
@@ -58,7 +59,8 @@ object FlintJob extends Logging {
       }
       val data = executeQuery(spark, query, dataSource)
 
-      val (correctMapping, error) = ThreadUtils.awaitResult(futureMappingCheck, Duration(1, MINUTES))
+      val (correctMapping, error) =
+        ThreadUtils.awaitResult(futureMappingCheck, Duration(1, MINUTES))
       dataToWrite = Some(if (correctMapping) data else getFailedData(spark, dataSource, error))
     } catch {
       case e: TimeoutException =>
@@ -100,19 +102,15 @@ object FlintJob extends Logging {
 
   /**
    * Create a new formatted dataframe with json result, json schema and EMR_STEP_ID.
-    *
-    * @param result
-    *   sql query result dataframe
-    * @param spark
-    *   spark session
-    * @return
-    *   dataframe with result, schema and emr step id
-    */
-  def getFormattedData(
-      result: DataFrame,
-      spark: SparkSession,
-      dataSource: String
-  ): DataFrame = {
+   *
+   * @param result
+   *   sql query result dataframe
+   * @param spark
+   *   spark session
+   * @return
+   *   dataframe with result, schema and emr step id
+   */
+  def getFormattedData(result: DataFrame, spark: SparkSession, dataSource: String): DataFrame = {
     // Create the schema dataframe
     val schemaRows = result.schema.fields.map { field =>
       Row(field.name, field.dataType.typeName)
@@ -122,31 +120,18 @@ object FlintJob extends Logging {
       StructType(
         Seq(
           StructField("column_name", StringType, nullable = false),
-          StructField("data_type", StringType, nullable = false)
-        )
-      )
-    )
+          StructField("data_type", StringType, nullable = false))))
 
     // Define the data schema
     val schema = StructType(
       Seq(
-        StructField(
-          "result",
-          ArrayType(StringType, containsNull = true),
-          nullable = true
-        ),
-        StructField(
-          "schema",
-          ArrayType(StringType, containsNull = true),
-          nullable = true
-        ),
+        StructField("result", ArrayType(StringType, containsNull = true), nullable = true),
+        StructField("schema", ArrayType(StringType, containsNull = true), nullable = true),
         StructField("jobRunId", StringType, nullable = true),
         StructField("applicationId", StringType, nullable = true),
         StructField("dataSourceName", StringType, nullable = true),
         StructField("status", StringType, nullable = true),
-          StructField("error", StringType, nullable = true)
-      )
-    )
+        StructField("error", StringType, nullable = true)))
 
     // Create the data rows
     val rows = Seq(
@@ -158,9 +143,7 @@ object FlintJob extends Logging {
         sys.env.getOrElse("SERVERLESS_EMR_VIRTUAL_CLUSTER_ID", "unknown"),
         dataSource,
         "SUCCESS",
-        ""
-      )
-    )
+        ""))
 
     // Create the DataFrame for data
     spark.createDataFrame(rows).toDF(schema.fields.map(_.name): _*)
@@ -171,23 +154,13 @@ object FlintJob extends Logging {
     // Define the data schema
     val schema = StructType(
       Seq(
-        StructField(
-          "result",
-          ArrayType(StringType, containsNull = true),
-          nullable = true
-        ),
-        StructField(
-          "schema",
-          ArrayType(StringType, containsNull = true),
-          nullable = true
-        ),
+        StructField("result", ArrayType(StringType, containsNull = true), nullable = true),
+        StructField("schema", ArrayType(StringType, containsNull = true), nullable = true),
         StructField("jobRunId", StringType, nullable = true),
         StructField("applicationId", StringType, nullable = true),
         StructField("dataSourceName", StringType, nullable = true),
         StructField("status", StringType, nullable = true),
-        StructField("error", StringType, nullable = true)
-      )
-    )
+        StructField("error", StringType, nullable = true)))
 
     // Create the data rows
     val rows = Seq(
@@ -198,9 +171,7 @@ object FlintJob extends Logging {
         sys.env.getOrElse("SERVERLESS_EMR_VIRTUAL_CLUSTER_ID", "unknown"),
         dataSource,
         "FAILED",
-        error
-      )
-    )
+        error))
 
     // Create the DataFrame for data
     spark.createDataFrame(rows).toDF(schema.fields.map(_.name): _*)
@@ -210,22 +181,23 @@ object FlintJob extends Logging {
 
     /**
      * Determines whether one JSON structure is a superset of another.
-      *
-      * This method checks if the `input` JSON structure contains all the fields
-      * and values present in the `mapping` JSON structure. The comparison is
-      * recursive and structure-sensitive, ensuring that nested objects and arrays
-      * are also compared accurately.
-      *
-      * Additionally, this method accommodates the edge case where boolean values
-      * in the JSON are represented as strings (e.g., "true" or "false" instead of
-      * true or false). This is handled by performing a case-insensitive comparison
-      * of string representations of boolean values.
-      *
-      * @param input   The input JSON structure as a String.
-      * @param mapping The mapping JSON structure as a String.
-      * @return A Boolean value indicating whether the `input` JSON structure
-      *         is a superset of the `mapping` JSON structure.
-      */
+     *
+     * This method checks if the `input` JSON structure contains all the fields and values present
+     * in the `mapping` JSON structure. The comparison is recursive and structure-sensitive,
+     * ensuring that nested objects and arrays are also compared accurately.
+     *
+     * Additionally, this method accommodates the edge case where boolean values in the JSON are
+     * represented as strings (e.g., "true" or "false" instead of true or false). This is handled
+     * by performing a case-insensitive comparison of string representations of boolean values.
+     *
+     * @param input
+     *   The input JSON structure as a String.
+     * @param mapping
+     *   The mapping JSON structure as a String.
+     * @return
+     *   A Boolean value indicating whether the `input` JSON structure is a superset of the
+     *   `mapping` JSON structure.
+     */
     def compareJson(inputJson: JsValue, mappingJson: JsValue): Boolean = {
       (inputJson, mappingJson) match {
         case (JsObject(inputFields), JsObject(mappingFields)) =>
@@ -238,18 +210,13 @@ object FlintJob extends Logging {
         case (JsArray(inputValues), JsArray(mappingValues)) =>
           logInfo(s"Comparing arrays: $inputValues vs $mappingValues")
           mappingValues.forall(mappingValue =>
-            inputValues.exists(inputValue =>
-              compareJson(inputValue, mappingValue)
-            )
-          )
+            inputValues.exists(inputValue => compareJson(inputValue, mappingValue)))
         case (JsString(inputValue), JsString(mappingValue))
             if (inputValue.toLowerCase(Locale.ROOT) == "true" ||
               inputValue.toLowerCase(Locale.ROOT) == "false") &&
               (mappingValue.toLowerCase(Locale.ROOT) == "true" ||
                 mappingValue.toLowerCase(Locale.ROOT) == "false") =>
-          inputValue.toLowerCase(Locale.ROOT) == mappingValue.toLowerCase(
-            Locale.ROOT
-          )
+          inputValue.toLowerCase(Locale.ROOT) == mappingValue.toLowerCase(Locale.ROOT)
         case (JsBoolean(inputValue), JsString(mappingValue))
             if mappingValue.toLowerCase(Locale.ROOT) == "true" ||
               mappingValue.toLowerCase(Locale.ROOT) == "false" =>
@@ -271,10 +238,7 @@ object FlintJob extends Logging {
     compareJson(inputJson, mappingJson)
   }
 
-  def checkAndCreateIndex(
-                           flintClient: FlintClient,
-                           resultIndex: String
-                         ): (Boolean, String) = {
+  def checkAndCreateIndex(flintClient: FlintClient, resultIndex: String): (Boolean, String) = {
     // The enabled setting, which can be applied only to the top-level mapping definition and to object fields,
     val mapping =
       """{
@@ -314,7 +278,8 @@ object FlintJob extends Logging {
         (true, "")
       }
     } catch {
-      case e: IllegalStateException if e.getCause().getMessage().contains("index_not_found_exception") =>
+      case e: IllegalStateException
+          if e.getCause().getMessage().contains("index_not_found_exception") =>
         handleIndexNotFoundException(flintClient, resultIndex, mapping)
       case e: Exception =>
         val error = "Failed to verify existing mapping"
@@ -324,10 +289,9 @@ object FlintJob extends Logging {
   }
 
   def handleIndexNotFoundException(
-                                    flintClient: FlintClient,
-                                    resultIndex: String,
-                                    mapping: String
-                                  ): (Boolean, String) = {
+      flintClient: FlintClient,
+      resultIndex: String,
+      mapping: String): (Boolean, String) = {
     try {
       logInfo(s"create $resultIndex")
       flintClient.createIndex(resultIndex, new FlintMetadata(mapping))
@@ -340,11 +304,7 @@ object FlintJob extends Logging {
         (false, error)
     }
   }
-  def executeQuery(
-      spark: SparkSession,
-      query: String,
-      dataSource: String
-  ): DataFrame = {
+  def executeQuery(spark: SparkSession, query: String, dataSource: String): DataFrame = {
     // Execute SQL query
     val result: DataFrame = spark.sql(query)
     // Get Data