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/*
* Copyright (C) 2024, UChicago Argonne, LLC
* Licensed under the 3-clause BSD license. See accompanying LICENSE.txt file
* in the top-level directory.
*/
package Octeres
Eric Pershey
committed
import Octeres.DataUDF.{LiteBitmaskSchema, logical_or}
import org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema
import org.apache.spark.sql.functions._
import org.apache.spark.sql.types._
import org.apache.spark.sql.{Encoders, Row, SparkSession}
import org.scalatest.funsuite.AnyFunSuite
Eric Pershey
committed
object ExampleUDF {
// very simple UDF function as an example.
case class SimpleAddStruct(a: Int, b: Int)
val SimpleAddSchema: StructType = Encoders.product[SimpleAddStruct].schema
def simpleAdd(a: Int, b: Int): Int = a + b
}
class DataUDFTest extends AnyFunSuite {
Eric Pershey
committed
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test("test_add") {
val result = ExampleUDF.simpleAdd(1, 2)
assert(result == 3)
}
test("test_simple") {
val sparkSession = SparkSession.builder().appName("DataUDFTest").master("local").getOrCreate()
import sparkSession.implicits._
val deck = Seq(
Row(1, 2),
)
var df = sparkSession.createDataFrame(sparkSession.sparkContext.parallelize(deck), schema = ExampleUDF.SimpleAddSchema)
sparkSession.udf.register("SimpleAdd", ExampleUDF.simpleAdd(_: Int, _: Int), IntegerType)
df = df.withColumn("c", expr("SimpleAdd(a, b)"))
df.show()
}
test("test_logical_or_00") {
println("test_logical_or_00")
val bitmask_length = 8
val a_bitmask = new GenericRowWithSchema(Array(bitmask_length, 3, List(List(0, 2)), 0, 2), LiteBitmaskSchema)
val b_bitmask = new GenericRowWithSchema(Array(bitmask_length, 3, List(List(1, 3)), 1, 3), LiteBitmaskSchema)
println(s"a_bitmask=${a_bitmask}")
println(s"b_bitmask=${b_bitmask}")
println(DataUDF.logical_or(a_bitmask, b_bitmask))
println(DataUDF.logical_or(null, b_bitmask))
println(DataUDF.logical_or(a_bitmask, null))
}
test("test_logical_or_01") {
println("test_logical_or_01")
val bitmask_length = 8
val a_bitmask = new GenericRowWithSchema(Array(bitmask_length, 3, List(List(0, 2)), 0, 2), LiteBitmaskSchema)
val b_bitmask = new GenericRowWithSchema(Array(bitmask_length, 0, List(), -1, -1), LiteBitmaskSchema)
println(s"a_bitmask=${a_bitmask}")
println(s"b_bitmask=${b_bitmask}")
println(DataUDF.logical_or(a_bitmask, b_bitmask))
println(DataUDF.logical_or(null, b_bitmask))
println(DataUDF.logical_or(a_bitmask, null))
println(DataUDF.logical_or(null, null))
println(DataUDF.logical_or(a_bitmask, a_bitmask))
println(DataUDF.logical_or(b_bitmask, b_bitmask))
}
test("test_bitmask") {
println("test_bitmask")
val bitmask_length = 8
// val a_bitmask = new GenericRowWithSchema(Array(bitmask_length, 3, Array(Array(0, 2)), 0, 2), LiteBitmaskSchema)
// val b_bitmask = new GenericRowWithSchema(Array(bitmask_length, 3, Array(Array(1, 3)), 1, 3), LiteBitmaskSchema)
val a_bitmask = new GenericRowWithSchema(Array(bitmask_length, 3, List(List(0, 2)), 0, 2), LiteBitmaskSchema)
val b_bitmask = new GenericRowWithSchema(Array(bitmask_length, 3, List(List(1, 3)), 1, 3), LiteBitmaskSchema)
val c_bitmask = new GenericRowWithSchema(Array(bitmask_length, 5, List(List(0, 4)), 0, 4), LiteBitmaskSchema)
val d_bitmask = new GenericRowWithSchema(Array(bitmask_length, 0, List(), -1, -1), LiteBitmaskSchema)
val e_bitmask = new GenericRowWithSchema(Array(bitmask_length, 6, List(List(0, 5)), 0, 5), LiteBitmaskSchema)
val schema = StructType(List(
StructField("a", IntegerType, nullable = true),
StructField("b", IntegerType, nullable = true),
StructField("bitmask", LiteBitmaskSchema, nullable = true)
))
val deck = Seq(
Row(0, 1, null),
Row(1, 2, a_bitmask),
Row(2, 4, b_bitmask),
Row(3, 8, c_bitmask),
Row(4, 16, d_bitmask),
Row(5, 32, e_bitmask),
)
val sparkSession = SparkSession.builder().appName("DataUDFTest").master("local").getOrCreate()
var df = sparkSession.createDataFrame(sparkSession.sparkContext.parallelize(deck), schema = schema)
DataUDF.registerAll(sparkSession)
df.createOrReplaceTempView("temp_view_a")
df.createOrReplaceTempView("temp_view_b")
df.show(32, truncate=false)
sparkSession.sql("select bitmask.intervals from temp_view_a").show(32, truncate=false)
var df2 = sparkSession.sql("Select * from temp_view_a")
// https://spark.apache.org/docs/latest/sql-ref-datatypes.html
df2.show(32, truncate=false)
df2 = df2.withColumn("r_bitmask", expr("logical_or(bitmask, bitmask)"))
df2.show(32, truncate=false)
var df3 = sparkSession.sql("select tva.a, tva.b, " +
"tva.bitmask as a_bitmask, " +
"tvb.bitmask as b_bitmask, " +
"logical_or(tva.bitmask, tvb.bitmask) as c_bitmask " +
// "intersection_any(tva.bitmask, tvb.bitmask) " +
"from temp_view_a tva join temp_view_b tvb"
)
df3.show(32, truncate=false)
df3.printSchema()
}