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feat(spark): add support for DelimiterSeparatedTextReadOptions
The handling of CSV in the spark module works only in a very limited way with many hard-coded assumptions. This commit adds full support for delimited text support as defined in the `FileOrFiles` proto message Signed-off-by: Andrew Coleman <andrew_coleman@uk.ibm.com>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,11 @@ | ||
| ID,VALUE | ||
| 1,one | ||
| 2,two | ||
| 3,three | ||
| 4,four | ||
| 5,five | ||
| 6,six | ||
| 7,seven | ||
| 8,eight | ||
| 9,nine | ||
| 10,ten |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,11 @@ | ||
| ID,VALUE | ||
| 11,eleven | ||
| 12,twelve | ||
| 13,thirteen | ||
| 14,fourteen | ||
| 15,fifteen | ||
| 16,sixteen | ||
| 17,seventeen | ||
| 18,eighteen | ||
| 19,nineteen | ||
| 20,twenty |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,11 @@ | ||
| ID,VALUE | ||
| 1,one | ||
| 2,"two" | ||
| 3,"three" | ||
| 4,"fo,ur" | ||
| 5,five | ||
| 6,six | ||
| 7,seven | ||
| 8,eight | ||
| 9,nine | ||
| 10,ten |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,10 @@ | ||
| 1|one | ||
| 2|two | ||
| 3|three | ||
| 4|'fo|ur' | ||
| 5|five | ||
| 6|'six' | ||
| 7|seven | ||
| 8|eight | ||
| 9|nine | ||
| 10|ten |
143 changes: 143 additions & 0 deletions
143
spark/src/test/scala/io/substrait/spark/LocalFiles.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. | ||
| */ | ||
|
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| package io.substrait.spark | ||
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| import io.substrait.spark.logical.{ToLogicalPlan, ToSubstraitRel} | ||
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| import org.apache.spark.sql.{Dataset, DatasetUtil, Row} | ||
| import org.apache.spark.sql.internal.SQLConf | ||
| import org.apache.spark.sql.test.SharedSparkSession | ||
| import org.apache.spark.sql.types.{IntegerType, StringType, StructField, StructType} | ||
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| import io.substrait.plan.{PlanProtoConverter, ProtoPlanConverter} | ||
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| import java.nio.file.Paths | ||
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| class LocalFiles extends SharedSparkSession { | ||
| override def beforeAll(): Unit = { | ||
| super.beforeAll() | ||
| sparkContext.setLogLevel("WARN") | ||
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| conf.setConf(SQLConf.DYNAMIC_PARTITION_PRUNING_ENABLED, false) | ||
| // introduced in spark 3.4 | ||
| spark.conf.set("spark.sql.readSideCharPadding", "false") | ||
| } | ||
|
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| def assertRoundTrip(data: Dataset[Row]): Dataset[Row] = { | ||
| val toSubstrait = new ToSubstraitRel | ||
| val sparkPlan = data.queryExecution.optimizedPlan | ||
| val substraitPlan = toSubstrait.convert(sparkPlan) | ||
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| // Serialize to proto buffer | ||
| val bytes = new PlanProtoConverter() | ||
| .toProto(substraitPlan) | ||
| .toByteArray | ||
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| // Read it back | ||
| val protoPlan = io.substrait.proto.Plan | ||
| .parseFrom(bytes) | ||
| val substraitPlan2 = new ProtoPlanConverter().from(protoPlan) | ||
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| val sparkPlan2 = new ToLogicalPlan(spark).convert(substraitPlan2) | ||
| val result = DatasetUtil.fromLogicalPlan(spark, sparkPlan2) | ||
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| assertResult(data.columns)(result.columns) | ||
| assertResult(data.count)(result.count) | ||
| data.collect().zip(result.collect()).foreach { | ||
| case (before, after) => assertResult(before)(after) | ||
| } | ||
| result | ||
| } | ||
|
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| test("CSV with header") { | ||
| val table = spark.read | ||
| .option("header", true) | ||
| .option("inferSchema", true) | ||
| .csv(Paths.get("src/test/resources/dataset-a.csv").toAbsolutePath.toString) | ||
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| assertRoundTrip(table) | ||
| } | ||
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| test("CSV null value") { | ||
| val table = spark.read | ||
| .option("header", true) | ||
| .option("inferSchema", true) | ||
| .option("nullValue", "seven") | ||
| .csv(Paths.get("src/test/resources/dataset-a.csv").toAbsolutePath.toString) | ||
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| val result = assertRoundTrip(table) | ||
| val id = result.filter("isnull(VALUE)").head().get(0) | ||
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| assertResult(id)(7) | ||
| } | ||
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| test("Pipe delimited values") { | ||
| val schema = StructType( | ||
| StructField("ID", IntegerType, false) :: | ||
| StructField("VALUE", StringType, true) :: Nil) | ||
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| val table: Dataset[Row] = spark.read | ||
| .schema(schema) | ||
| .option("delimiter", "|") | ||
| .option("quote", "'") | ||
| .csv(Paths.get("src/test/resources/dataset-a.txt").toAbsolutePath.toString) | ||
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| assertRoundTrip(table) | ||
| } | ||
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| test("Read csv folder") { | ||
| val table = spark.read | ||
| .option("header", true) | ||
| .option("inferSchema", true) | ||
| .csv(Paths.get("src/test/resources/csv/").toAbsolutePath.toString) | ||
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| assertRoundTrip(table) | ||
| } | ||
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| test("Read parquet file") { | ||
| val table = spark.read | ||
| .parquet(Paths.get("src/test/resources/dataset-a.parquet").toAbsolutePath.toString) | ||
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| assertRoundTrip(table) | ||
| } | ||
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| test("Read orc file") { | ||
| val table = spark.read | ||
| .orc(Paths.get("src/test/resources/dataset-a.orc").toAbsolutePath.toString) | ||
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| assertRoundTrip(table) | ||
| } | ||
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| test("Join tables from different formats") { | ||
| val csv = spark.read | ||
| .option("header", true) | ||
| .option("inferSchema", true) | ||
| .csv(Paths.get("src/test/resources/dataset-a.csv").toAbsolutePath.toString) | ||
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| val orc = spark.read | ||
| .orc(Paths.get("src/test/resources/dataset-a.orc").toAbsolutePath.toString) | ||
| .withColumnRenamed("ID", "ID_B") | ||
| .withColumnRenamed("VALUE", "VALUE_B"); | ||
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| val both = csv | ||
| .join(orc, csv.col("ID").equalTo(orc.col("ID_B"))) | ||
| .select("ID", "VALUE", "VALUE_B") | ||
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| assertRoundTrip(both) | ||
| } | ||
| } |
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