Add ability to round generated numbers, set metadata statistics and r…

…ecord tracking log from info to debug

api/src/main/scala/io/github/datacatering/datacaterer/api/TaskBuilder.scala

@@ -904,6 +904,15 @@ case class FieldBuilder(field: Field = Field()) {
   def numericScale(scale: Int): FieldBuilder =
     this.modify(_.field.generator).setTo(Some(getGenBuilder.numericScale(scale).generator))
 
+  /**
+   * Sets the rounding for the field.
+   *
+   * @param round Number of decimal places to round to
+   * @return the updated `FieldBuilder` instance
+   */
+  def round(round: Int): FieldBuilder =
+    this.modify(_.field.generator).setTo(Some(getGenBuilder.round(round).generator))
+
   /**
    * Sets whether the field should be omitted from the generated output.
    *
@@ -1225,6 +1234,15 @@ case class GeneratorBuilder(generator: Generator = Generator()) {
   def numericScale(scale: Int): GeneratorBuilder =
     this.modify(_.generator.options)(_ ++ Map(NUMERIC_SCALE -> scale.toString))
 
+  /**
+   * Rounding to decimal places for numeric data types
+   *
+   * @param round Number of decimal places to round to
+   * @return GeneratorBuilder
+   */
+  def round(round: Int): GeneratorBuilder =
+    this.modify(_.generator.options)(_ ++ Map(ROUND -> round.toString))
+
   /**
    * Enable/disable including the value in the final output to the data source. Allows you to define intermediate values
    * that can be used to generate other columns

api/src/main/scala/io/github/datacatering/datacaterer/api/model/Constants.scala

@@ -83,6 +83,7 @@ object Constants {
   lazy val MAXIMUM = "max"
   lazy val STANDARD_DEVIATION = "stddev"
   lazy val MEAN = "mean"
+  lazy val ROUND = "round"
   lazy val DISTRIBUTION = "distribution"
   lazy val DISTRIBUTION_RATE_PARAMETER = "distributionRateParam"
   lazy val DISTRIBUTION_UNIFORM = "uniform"

app/src/main/scala/io/github/datacatering/datacaterer/core/generator/provider/RandomDataGenerator.scala

@@ -1,6 +1,6 @@
 package io.github.datacatering.datacaterer.core.generator.provider
 
-import io.github.datacatering.datacaterer.api.model.Constants.{ARRAY_MAXIMUM_LENGTH, ARRAY_MINIMUM_LENGTH, DEFAULT_VALUE, DISTINCT_COUNT, DISTRIBUTION, DISTRIBUTION_EXPONENTIAL, DISTRIBUTION_NORMAL, DISTRIBUTION_RATE_PARAMETER, EXPRESSION, IS_UNIQUE, MAXIMUM, MAXIMUM_LENGTH, MEAN, MINIMUM, MINIMUM_LENGTH, NUMERIC_PRECISION, NUMERIC_SCALE, ROW_COUNT, STANDARD_DEVIATION}
+import io.github.datacatering.datacaterer.api.model.Constants.{ARRAY_MAXIMUM_LENGTH, ARRAY_MINIMUM_LENGTH, DEFAULT_VALUE, DISTINCT_COUNT, DISTRIBUTION, DISTRIBUTION_EXPONENTIAL, DISTRIBUTION_NORMAL, DISTRIBUTION_RATE_PARAMETER, EXPRESSION, IS_UNIQUE, MAXIMUM, MAXIMUM_LENGTH, MEAN, MINIMUM, MINIMUM_LENGTH, NUMERIC_PRECISION, NUMERIC_SCALE, ROUND, ROW_COUNT, STANDARD_DEVIATION}
 import io.github.datacatering.datacaterer.core.exception.UnsupportedDataGeneratorType
 import io.github.datacatering.datacaterer.core.model.Constants._
 import io.github.datacatering.datacaterer.core.util.GeneratorUtil
@@ -386,10 +386,15 @@ object RandomDataGenerator {
       s"$sqlRand * $diff + $min"
     }
 
-    if (!baseFormula.contains(INDEX_INC_COL) && (typeName == "INT" || typeName == "SHORT" || typeName == "LONG")) {
-      s"CAST(ROUND($baseFormula, 0) AS $typeName)"
+    val rounded = if (metadata.contains(ROUND)) {
+      val roundValue = metadata.getString(ROUND)
+      s"ROUND($baseFormula, $roundValue)"
+    } else baseFormula
+
+    if (!rounded.contains(INDEX_INC_COL) && (typeName == "INT" || typeName == "SHORT" || typeName == "LONG")) {
+      s"CAST(ROUND($rounded, 0) AS $typeName)"
     } else {
-      s"CAST($baseFormula AS $typeName)"
+      s"CAST($rounded AS $typeName)"
     }
   }
 

app/src/main/scala/io/github/datacatering/datacaterer/core/generator/track/RecordTrackingProcessor.scala

@@ -13,7 +13,7 @@ class RecordTrackingProcessor(recordTrackingFolderPath: String) {
 
   def trackRecords(df: DataFrame, dataSourceName: String, planName: String, step: Step): Unit = {
     val subDataSourcePath = getSubDataSourcePath(dataSourceName, planName, step, recordTrackingFolderPath)
-    LOGGER.info(s"Generated record tracking is enabled, data-source-name=$dataSourceName, plan-name=$planName, save-path=$subDataSourcePath")
+    LOGGER.debug(s"Generated record tracking is enabled, data-source-name=$dataSourceName, plan-name=$planName, save-path=$subDataSourcePath")
     if (df.isEmpty || df.schema.isEmpty) {
       LOGGER.debug("Unable to save records for record tracking due to 0 records found or empty schema")
     } else {

app/src/main/scala/io/github/datacatering/datacaterer/core/util/MetadataUtil.scala

@@ -111,7 +111,7 @@ object MetadataUtil {
     computeColumnStatistics(sourceData, dataSourceReadOptions, dataSourceMetadata.name, dataSourceMetadata.format)
     val columnLevelStatistics = sparkSession.sharedState.cacheManager.lookupCachedData(sourceData).get.cachedRepresentation.stats
     val rowCount = columnLevelStatistics.rowCount.getOrElse(BigInt(0))
-    LOGGER.info(s"Computed metadata statistics for data source, name=${dataSourceMetadata.name}, format=$dataSourceFormat, " +
+    LOGGER.debug(s"Computed metadata statistics for data source, name=${dataSourceMetadata.name}, format=$dataSourceFormat, " +
       s"details=${ConfigUtil.cleanseOptions(dataSourceReadOptions)}, rows-analysed=$rowCount, size-in-bytes=${columnLevelStatistics.sizeInBytes}, " +
       s"num-columns-analysed=${columnLevelStatistics.attributeStats.size}")
 

app/src/test/scala/io/github/datacatering/datacaterer/core/generator/provider/RandomDataGeneratorTest.scala

@@ -1,6 +1,6 @@
 package io.github.datacatering.datacaterer.core.generator.provider
 
-import io.github.datacatering.datacaterer.api.model.Constants.{ARRAY_MINIMUM_LENGTH, DISTINCT_COUNT, DISTRIBUTION, DISTRIBUTION_EXPONENTIAL, DISTRIBUTION_NORMAL, DISTRIBUTION_RATE_PARAMETER, ENABLED_EDGE_CASE, ENABLED_NULL, EXPRESSION, IS_UNIQUE, MAXIMUM, MAXIMUM_LENGTH, MEAN, MINIMUM, MINIMUM_LENGTH, PROBABILITY_OF_EDGE_CASE, PROBABILITY_OF_NULL, ROW_COUNT, STANDARD_DEVIATION}
+import io.github.datacatering.datacaterer.api.model.Constants.{ARRAY_MINIMUM_LENGTH, DISTINCT_COUNT, DISTRIBUTION, DISTRIBUTION_EXPONENTIAL, DISTRIBUTION_NORMAL, DISTRIBUTION_RATE_PARAMETER, ENABLED_EDGE_CASE, ENABLED_NULL, EXPRESSION, IS_UNIQUE, MAXIMUM, MAXIMUM_LENGTH, MEAN, MINIMUM, MINIMUM_LENGTH, PROBABILITY_OF_EDGE_CASE, PROBABILITY_OF_NULL, ROUND, ROW_COUNT, STANDARD_DEVIATION}
 import io.github.datacatering.datacaterer.core.generator.provider.RandomDataGenerator._
 import io.github.datacatering.datacaterer.core.model.Constants.INDEX_INC_COL
 import org.apache.spark.sql.types._
@@ -189,6 +189,17 @@ class RandomDataGeneratorTest extends AnyFunSuite {
     assert(doubleGenerator.generateSqlExpression == "CAST(RAND() * 5.0 + 5.0 AS DOUBLE)")
   }
 
+  test("Can create random double generator with custom min, max and rounding") {
+    val metadata = new MetadataBuilder().putString(MAXIMUM, "10.0").putString(MINIMUM, "5.0").putString(ROUND, "2").build()
+    val doubleGenerator = new RandomDoubleDataGenerator(StructField("random_double", DoubleType, false, metadata))
+    val sampleData = doubleGenerator.generate
+
+    assert(doubleGenerator.edgeCases.nonEmpty)
+    assert(sampleData >= 5.0)
+    assert(sampleData <= 10.0)
+    assert(doubleGenerator.generateSqlExpression == "CAST(ROUND(RAND() * 5.0 + 5.0, 2) AS DOUBLE)")
+  }
+
   test("Can create random float generator") {
     val floatGenerator = new RandomFloatDataGenerator(StructField("random_float", FloatType, false))
     val sampleData = floatGenerator.generate

app/src/test/scala/io/github/datacatering/datacaterer/core/plan/PlanProcessorTest.scala

@@ -24,7 +24,7 @@ class PlanProcessorTest extends SparkSuite {
         .schema(
           field.name("account_id").regex("ACC[0-9]{8}"),
           field.name("year").`type`(IntegerType).sql("YEAR(date)"),
-          field.name("balance").`type`(DoubleType).min(10).max(1000),
+          field.name("balance").`type`(DoubleType).min(10).max(1000).round(2),
           field.name("date").`type`(DateType).min(Date.valueOf("2022-01-01")),
           field.name("status").oneOf(accountStatus: _*),
           field.name("update_history")

gradle.properties

@@ -1,5 +1,5 @@
 groupId=io.github.data-catering
-version=0.12.2
+version=0.12.3
 
 scalaVersion=2.12
 scalaSpecificVersion=2.12.19