Github user kiszk commented on a diff in the pull request: https://github.com/apache/spark/pull/13680#discussion_r74038625 --- Diff: sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/util/UnsafeArraySuite.scala --- @@ -18,27 +18,131 @@ package org.apache.spark.sql.catalyst.util import org.apache.spark.SparkFunSuite +import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder import org.apache.spark.sql.catalyst.expressions.UnsafeArrayData +import org.apache.spark.unsafe.Platform class UnsafeArraySuite extends SparkFunSuite { - test("from primitive int array") { - val array = Array(1, 10, 100) - val unsafe = UnsafeArrayData.fromPrimitiveArray(array) - assert(unsafe.numElements == 3) - assert(unsafe.getSizeInBytes == 4 + 4 * 3 + 4 * 3) - assert(unsafe.getInt(0) == 1) - assert(unsafe.getInt(1) == 10) - assert(unsafe.getInt(2) == 100) + val booleanArray = Array(false, true) + val shortArray = Array(1.toShort, 10.toShort, 100.toShort) + val intArray = Array(1, 10, 100) + val longArray = Array(1.toLong, 10.toLong, 100.toLong) + val floatArray = Array(1.1.toFloat, 2.2.toFloat, 3.3.toFloat) + val doubleArray = Array(1.1, 2.2, 3.3) + val stringArray = Array("1", "10", "100") --- End diff -- @davies thanks. I understand what I should do. While I specified the scheme as follows, the generated code still uses 38 and 18. When I checked code generation, [this code](https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateUnsafeProjection.scala#L300) gets data type from serializer instead of schema. If I am correct, [this code](https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/encoders/ExpressionEncoder.scala#L61) generates a serializer in `ExpressionEncoder[T]` based on `[T]`, not a schema. When I replaced ['DecimalType.SYSTEM_DEFAULT'](https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala#L511 ) with 'DecimalType(4,1)', the generated code uses 4 and 1. Would it be possible to let me know how to specify specific dataType by using schema? ``` val decimalArray = Array(BigDecimal("123").setScale(1, BigDecimal.RoundingMode.FLOOR)) test("read array") { val unsafeDecimal = ExpressionEncoder[Array[BigDecimal]].copy(schema = new StructType() .add("value", ArrayType(DataTypes.createDecimalType(4, 1), true), true), true) .resolveAndBind().toRow(decimalArray).getArray(0) decimalArray.zipWithIndex.map { case (e, i) => assert(unsafeDecimal.getDecimal(i, e.precision, e.scale) == e) } } ```
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