[SPARK-31183][SQL] Rebase date/timestamp from/to Julian calendar in Avro #27953
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| Original file line number | Diff line number | Diff line change |
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@@ -17,15 +17,15 @@ | |
| package org.apache.spark.sql.avro | ||
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| import java.io.File | ||
| import java.sql.{Date, Timestamp} | ||
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| import org.apache.avro.{LogicalTypes, Schema} | ||
| import org.apache.avro.Conversions.DecimalConversion | ||
| import org.apache.avro.file.DataFileWriter | ||
| import org.apache.avro.generic.{GenericData, GenericDatumWriter, GenericRecord} | ||
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| import org.apache.spark.{SparkConf, SparkException} | ||
| import org.apache.spark.sql.{DataFrame, QueryTest, Row} | ||
| import org.apache.spark.sql.catalyst.util.DateTimeUtils | ||
| import org.apache.spark.sql.internal.SQLConf | ||
| import org.apache.spark.sql.test.SharedSparkSession | ||
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@@ -348,6 +348,100 @@ abstract class AvroLogicalTypeSuite extends QueryTest with SharedSparkSession { | |
| assert(msg.contains("Unscaled value too large for precision")) | ||
| } | ||
| } | ||
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| private def readResourceAvroFile(name: String): DataFrame = { | ||
| val url = Thread.currentThread().getContextClassLoader.getResource(name) | ||
| spark.read.format("avro").load(url.toString) | ||
| } | ||
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| test("SPARK-31183: compatibility with Spark 2.4 in reading dates/timestamps") { | ||
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Contributor
There was a problem hiding this comment. missed one thing. I think the test is not very related to logical types and probably should be put in @MaxGekk can you move the test in your next PR?
Member
Author
There was a problem hiding this comment. Do you mean only this test, correct?
Contributor
There was a problem hiding this comment. All the new tests added here. The are more about compatibility, not logical type. |
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| withSQLConf(SQLConf.LEGACY_AVRO_REBASE_DATETIME.key -> "true") { | ||
| checkAnswer( | ||
| readResourceAvroFile("before_1582_date_v2_4.avro"), | ||
| Row(java.sql.Date.valueOf("1001-01-01"))) | ||
| checkAnswer( | ||
| readResourceAvroFile("before_1582_ts_micros_v2_4.avro"), | ||
| Row(java.sql.Timestamp.valueOf("1001-01-01 01:02:03.123456"))) | ||
| checkAnswer( | ||
| readResourceAvroFile("before_1582_ts_millis_v2_4.avro"), | ||
| Row(java.sql.Timestamp.valueOf("1001-01-01 01:02:03.124"))) | ||
| } | ||
| } | ||
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| test("SPARK-31183: rebasing microseconds timestamps in write") { | ||
| val tsStr = "1001-01-01 01:02:03.123456" | ||
| val nonRebased = "1001-01-07 01:09:05.123456" | ||
| withTempPath { dir => | ||
| val path = dir.getAbsolutePath | ||
| withSQLConf(SQLConf.LEGACY_AVRO_REBASE_DATETIME.key -> "true") { | ||
| Seq(tsStr).toDF("tsS") | ||
| .select($"tsS".cast("timestamp").as("ts")) | ||
| .write.format("avro") | ||
| .save(path) | ||
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| checkAnswer(spark.read.format("avro").load(path), Row(Timestamp.valueOf(tsStr))) | ||
| } | ||
| withSQLConf(SQLConf.LEGACY_AVRO_REBASE_DATETIME.key -> "false") { | ||
| checkAnswer(spark.read.format("avro").load(path), Row(Timestamp.valueOf(nonRebased))) | ||
| } | ||
| } | ||
| } | ||
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| test("SPARK-31183: rebasing milliseconds timestamps in write") { | ||
| val tsStr = "1001-01-01 01:02:03.123456" | ||
| val rebased = "1001-01-01 01:02:03.123" | ||
| val nonRebased = "1001-01-07 01:09:05.123" | ||
| Seq( | ||
| """{"type": "long","logicalType": "timestamp-millis"}""", | ||
| """"long"""").foreach { tsType => | ||
| val timestampSchema = s""" | ||
| |{ | ||
| | "namespace": "logical", | ||
| | "type": "record", | ||
| | "name": "test", | ||
| | "fields": [ | ||
| | {"name": "ts", "type": $tsType} | ||
| | ] | ||
| |}""".stripMargin | ||
| withTempPath { dir => | ||
| val path = dir.getAbsolutePath | ||
| withSQLConf(SQLConf.LEGACY_AVRO_REBASE_DATETIME.key -> "true") { | ||
| Seq(tsStr).toDF("tsS") | ||
| .select($"tsS".cast("timestamp").as("ts")) | ||
| .write | ||
| .option("avroSchema", timestampSchema) | ||
| .format("avro") | ||
| .save(path) | ||
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| checkAnswer( | ||
| spark.read.schema("ts timestamp").format("avro").load(path), | ||
| Row(Timestamp.valueOf(rebased))) | ||
| } | ||
| withSQLConf(SQLConf.LEGACY_AVRO_REBASE_DATETIME.key -> "false") { | ||
| checkAnswer( | ||
| spark.read.schema("ts timestamp").format("avro").load(path), | ||
| Row(Timestamp.valueOf(nonRebased))) | ||
| } | ||
| } | ||
| } | ||
| } | ||
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| test("SPARK-31183: rebasing dates in write") { | ||
| withTempPath { dir => | ||
| val path = dir.getAbsolutePath | ||
| withSQLConf(SQLConf.LEGACY_AVRO_REBASE_DATETIME.key -> "true") { | ||
| Seq("1001-01-01").toDF("dateS") | ||
| .select($"dateS".cast("date").as("date")) | ||
| .write.format("avro") | ||
| .save(path) | ||
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| checkAnswer(spark.read.format("avro").load(path), Row(Date.valueOf("1001-01-01"))) | ||
| } | ||
| withSQLConf(SQLConf.LEGACY_AVRO_REBASE_DATETIME.key -> "false") { | ||
| checkAnswer(spark.read.format("avro").load(path), Row(Date.valueOf("1001-01-07"))) | ||
| } | ||
| } | ||
| } | ||
| } | ||
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| class AvroV1LogicalTypeSuite extends AvroLogicalTypeSuite { | ||
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One more thing, why don't we return a function rather than checking
rebaseDateTimefor every time?There was a problem hiding this comment.
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I can move the flag checking out of the function body in a follow PR, or in the same for #27953 (comment)
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I think it's easy to switch with almost no additional complexity. Seems fine to change rather than relying on other optimization like JIT, or having a bad example.