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[SPARK-29347][SQL] Add JSON serialization for external Rows
### What changes were proposed in this pull request? This PR adds JSON serialization for Spark external Rows. ### Why are the changes needed? This is to be used for observable metrics where the `StreamingQueryProgress` contains a map of observed metrics rows which needs to be serialized in some cases. ### Does this PR introduce any user-facing change? Yes, a user can call `toJson` on rows returned when collecting a DataFrame to the driver. ### How was this patch tested? Added a new test suite: `RowJsonSuite` that should test this. Closes apache#26013 from hvanhovell/SPARK-29347. Authored-by: herman <[email protected]> Signed-off-by: herman <[email protected]>
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sql/catalyst/src/test/scala/org/apache/spark/sql/RowJsonSuite.scala
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| /* | ||
| * Licensed to the Apache Software Foundation (ASF) under one or more | ||
| * contributor license agreements. See the NOTICE file distributed with | ||
| * this work for additional information regarding copyright ownership. | ||
| * The ASF licenses this file to You under the Apache License, Version 2.0 | ||
| * (the "License"); you may not use this file except in compliance with | ||
| * the License. You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
| package org.apache.spark.sql | ||
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| import java.sql.{Date, Timestamp} | ||
| import java.time.{Instant, LocalDate} | ||
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| import org.json4s.JsonAST.{JArray, JBool, JDecimal, JDouble, JLong, JNull, JObject, JString, JValue} | ||
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| import org.apache.spark.SparkFunSuite | ||
| import org.apache.spark.sql.catalyst.encoders.{ExamplePoint, ExamplePointUDT} | ||
| import org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema | ||
| import org.apache.spark.sql.internal.SQLConf | ||
| import org.apache.spark.sql.types._ | ||
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| /** | ||
| * Test suite for [[Row]] JSON serialization. | ||
| */ | ||
| class RowJsonSuite extends SparkFunSuite { | ||
| private val schema = new StructType() | ||
| .add("c1", "string") | ||
| .add("c2", IntegerType) | ||
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| private def testJson(name: String, value: Any, dt: DataType, expected: JValue): Unit = { | ||
| test(name) { | ||
| val row = new GenericRowWithSchema(Array(value), new StructType().add("a", dt)) | ||
| assert(row.jsonValue === JObject("a" -> expected)) | ||
| } | ||
| } | ||
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| private def testJson(value: Any, dt: DataType, expected: JValue): Unit = { | ||
| testJson(s"$dt $value", value, dt, expected) | ||
| } | ||
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| // Nulls | ||
| private def testJsonNull(dt: DataType, expected: JValue): Unit = { | ||
| testJson(null, dt, JNull) | ||
| } | ||
| testJsonNull(IntegerType, JNull) | ||
| testJsonNull(FloatType, JNull) | ||
| testJsonNull(ArrayType(DoubleType, containsNull = true), JNull) | ||
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| // Primitives | ||
| testJson(true, BooleanType, JBool(true)) | ||
| testJson(false, BooleanType, JBool(false)) | ||
| testJson(23.toByte, ByteType, JLong(23)) | ||
| testJson(-126.toByte, ByteType, JLong(-126)) | ||
| testJson(20281.toShort, ShortType, JLong(20281)) | ||
| testJson(-8752.toShort, ShortType, JLong(-8752)) | ||
| testJson(1078231987, IntegerType, JLong(1078231987)) | ||
| testJson(-10, IntegerType, JLong(-10)) | ||
| testJson(139289832109874199L, LongType, JLong(139289832109874199L)) | ||
| testJson(-7873748239973488L, LongType, JLong(-7873748239973488L)) | ||
| testJson(10.232e10f, FloatType, JDouble(10.232e10f)) | ||
| testJson(9.7e-13f, FloatType, JDouble(9.7e-13f)) | ||
| testJson(3.891e98d, DoubleType, JDouble(3.891e98d)) | ||
| testJson(-7.8e5d, DoubleType, JDouble(-7.8e5d)) | ||
| testJson(BigDecimal("1092.88"), DecimalType(10, 2), JDecimal(BigDecimal("1092.88"))) | ||
| testJson(Decimal("782.0003"), DecimalType(7, 4), JDecimal(BigDecimal("782.0003"))) | ||
| testJson(new java.math.BigDecimal("-77.89"), DecimalType(4, 2), JDecimal(BigDecimal("-77.89"))) | ||
| testJson("hello world", StringType, JString("hello world")) | ||
| testJson("BinaryType", Array('a'.toByte, 'b'.toByte), BinaryType, JString("YWI=")) | ||
| testJson(Date.valueOf("2019-04-22"), DateType, JString("2019-04-22")) | ||
| testJson(LocalDate.of(2018, 5, 14), DateType, JString("2018-05-14")) | ||
| testJson( | ||
| Timestamp.valueOf("2017-01-06 10:22:03.00"), | ||
| TimestampType, | ||
| JString("2017-01-06 10:22:03")) | ||
| testJson( | ||
| Timestamp.valueOf("2017-05-30 10:22:03.00").toInstant, | ||
| TimestampType, | ||
| JString("2017-05-30 10:22:03")) | ||
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| // Complex types | ||
| testJson( | ||
| "ArrayType(LongType,true)", | ||
| Array(1L, null, 77L), | ||
| ArrayType(LongType, containsNull = true), | ||
| JArray(JLong(1L) :: JNull :: JLong(77L) :: Nil)) | ||
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| testJson( | ||
| Seq(1, -2, 3), | ||
| ArrayType(IntegerType, containsNull = false), | ||
| JArray(JLong(1) :: JLong(-2) :: JLong(3) :: Nil)) | ||
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| testJson( | ||
| Map("a" -> "b", "c" -> "d", "e" -> null), | ||
| MapType(StringType, StringType, valueContainsNull = true), | ||
| JObject("a" -> JString("b"), "c" -> JString("d"), "e" -> JNull)) | ||
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| testJson( | ||
| Map(1 -> "b", 2 -> "d", 3 -> null), | ||
| MapType(IntegerType, StringType, valueContainsNull = true), | ||
| JArray( | ||
| JObject("key" -> JLong(1), "value" -> JString("b")) :: | ||
| JObject("key" -> JLong(2), "value" -> JString("d")) :: | ||
| JObject("key" -> JLong(3), "value" -> JNull) :: Nil)) | ||
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| testJson( | ||
| new GenericRowWithSchema(Array("1", 2), schema), | ||
| schema, | ||
| JObject("c1" -> JString("1"), "c2" -> JLong(2))) | ||
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| testJson( | ||
| "UDT", | ||
| new ExamplePoint(3.4d, 8.98d), | ||
| new ExamplePointUDT, | ||
| JArray(JDouble(3.4d) :: JDouble(8.98d) :: Nil)) | ||
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| test("no schema") { | ||
| val e = intercept[IllegalArgumentException] { | ||
| Row("a").jsonValue | ||
| } | ||
| assert(e.getMessage.contains("requires a non-null schema")) | ||
| } | ||
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| test("unsupported type") { | ||
| val e = intercept[IllegalArgumentException] { | ||
| val row = new GenericRowWithSchema( | ||
| Array((1, 2)), | ||
| new StructType().add("a", ObjectType(classOf[(Int, Int)]))) | ||
| row.jsonValue | ||
| } | ||
| assert(e.getMessage.contains("Failed to convert value")) | ||
| } | ||
| } |