revert arrow version to 9

lakesoul-io · Mar 21, 2023 · 0431dbf · 0431dbf
1 parent ef92479
commit 0431dbf
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diff --git a/.github/workflows/flink-cdc-test.yml b/.github/workflows/flink-cdc-test.yml
@@ -51,7 +51,8 @@ jobs:
           docker pull -q dockcross/manylinux2014-x64:latest
       - name: Build with Maven
         run: |
-          MAVEN_OPTS="-Xmx4000m" mvn -q -B clean package -f pom.xml -DskipTests
+          cargo install cross --git https://github.com/cross-rs/cross
+          MAVEN_OPTS="-Xmx4000m" mvn -q -B clean package -f pom.xml -Prelease-linux-x86-64 -DskipTests
       - name: Get jar names
         run: |
           echo "FLINK_JAR_NAME=$(python script/get_jar_name.py lakesoul-flink)" >> $GITHUB_ENV
@@ -85,7 +86,7 @@ jobs:
       - name: Accuracy verification task
         run: |
           cd ./script/benchmark
-          docker run --cpus 2 -m 5000m --net lakesoul-docker-compose-env_default --rm -t -v ${PWD}/work-dir:/opt/spark/work-dir --env lakesoul_home=/opt/spark/work-dir/lakesoul.properties bitnami/spark:3.3.1 spark-submit --driver-memory 4G --executor-memory 4G --conf spark.driver.memoryOverhead=1500m --conf spark.executor.memoryOverhead=1500m --jars /opt/spark/work-dir/$SPARK_JAR_NAME,/opt/spark/work-dir/mysql-connector-java-8.0.30.jar --conf spark.hadoop.fs.s3.buffer.dir=/tmp --conf spark.hadoop.fs.s3a.buffer.dir=/tmp --conf  spark.hadoop.fs.s3a.fast.upload.buffer=disk --conf spark.hadoop.fs.s3a.fast.upload=true --class org.apache.spark.sql.lakesoul.benchmark.Benchmark --master local[4] /opt/spark/work-dir/$SPARK_TEST_JAR_NAME
+          docker run --cpus 2 -m 5000m --net lakesoul-docker-compose-env_default --rm -t -v ${PWD}/work-dir:/opt/spark/work-dir --env lakesoul_home=/opt/spark/work-dir/lakesoul.properties bitnami/spark:3.3.1 spark-submit --driver-memory 4G --executor-memory 4G --conf spark.driver.memoryOverhead=1500m --conf spark.executor.memoryOverhead=1500m --jars /opt/spark/work-dir/$SPARK_JAR_NAME,/opt/spark/work-dir/mysql-connector-java-8.0.30.jar --conf spark.hadoop.fs.s3.buffer.dir=/tmp --conf spark.hadoop.fs.s3a.buffer.dir=/tmp --conf  spark.hadoop.fs.s3a.fast.upload.buffer=disk --conf spark.hadoop.fs.s3a.fast.upload=true --conf spark.dmetasoul.lakesoul.native.io.enable=true --class org.apache.spark.sql.lakesoul.benchmark.Benchmark --master local[4] /opt/spark/work-dir/$SPARK_TEST_JAR_NAME
       - name: Adding columns for tables and deleting some data from tables
         run: |
           cd ./script/benchmark
@@ -96,7 +97,7 @@ jobs:
       - name: Accuracy verification task
         run: |
           cd ./script/benchmark
-          docker run --cpus 2 -m 5000m --net lakesoul-docker-compose-env_default --rm -t -v ${PWD}/work-dir:/opt/spark/work-dir --env lakesoul_home=/opt/spark/work-dir/lakesoul.properties bitnami/spark:3.3.1 spark-submit --driver-memory 4G --executor-memory 4G --conf spark.driver.memoryOverhead=1500m --conf spark.executor.memoryOverhead=1500m --jars /opt/spark/work-dir/$SPARK_JAR_NAME,/opt/spark/work-dir/mysql-connector-java-8.0.30.jar --class org.apache.spark.sql.lakesoul.benchmark.Benchmark --master local[4] /opt/spark/work-dir/$SPARK_TEST_JAR_NAME
+          docker run --cpus 2 -m 5000m --net lakesoul-docker-compose-env_default --rm -t -v ${PWD}/work-dir:/opt/spark/work-dir --env lakesoul_home=/opt/spark/work-dir/lakesoul.properties bitnami/spark:3.3.1 spark-submit --driver-memory 4G --executor-memory 4G --conf spark.driver.memoryOverhead=1500m --conf spark.executor.memoryOverhead=1500m --conf spark.dmetasoul.lakesoul.native.io.enable=true --jars /opt/spark/work-dir/$SPARK_JAR_NAME,/opt/spark/work-dir/mysql-connector-java-8.0.30.jar --class org.apache.spark.sql.lakesoul.benchmark.Benchmark --master local[4] /opt/spark/work-dir/$SPARK_TEST_JAR_NAME
       - name: Updating data in tables
         run: |
           cd ./script/benchmark
@@ -105,7 +106,7 @@ jobs:
       - name: Accuracy verification task
         run: |
           cd ./script/benchmark
-          docker run --cpus 2 -m 5000m --net lakesoul-docker-compose-env_default --rm -t -v ${PWD}/work-dir:/opt/spark/work-dir --env lakesoul_home=/opt/spark/work-dir/lakesoul.properties bitnami/spark:3.3.1 spark-submit --driver-memory 4G --executor-memory 4G --conf spark.driver.memoryOverhead=1500m --conf spark.executor.memoryOverhead=1500m --jars /opt/spark/work-dir/$SPARK_JAR_NAME,/opt/spark/work-dir/mysql-connector-java-8.0.30.jar --class org.apache.spark.sql.lakesoul.benchmark.Benchmark --master local[4] /opt/spark/work-dir/$SPARK_TEST_JAR_NAME
+          docker run --cpus 2 -m 5000m --net lakesoul-docker-compose-env_default --rm -t -v ${PWD}/work-dir:/opt/spark/work-dir --env lakesoul_home=/opt/spark/work-dir/lakesoul.properties bitnami/spark:3.3.1 spark-submit --driver-memory 4G --executor-memory 4G --conf spark.driver.memoryOverhead=1500m --conf spark.executor.memoryOverhead=1500m --conf spark.dmetasoul.lakesoul.native.io.enable=true --jars /opt/spark/work-dir/$SPARK_JAR_NAME,/opt/spark/work-dir/mysql-connector-java-8.0.30.jar --class org.apache.spark.sql.lakesoul.benchmark.Benchmark --master local[4] /opt/spark/work-dir/$SPARK_TEST_JAR_NAME
       - name: Dropping columns and deleting some data in tables
         run: |
           cd ./script/benchmark
@@ -116,4 +117,4 @@ jobs:
       - name: Accuracy verification task
         run: |
           cd ./script/benchmark
-          docker run --cpus 2 -m 5000m --net lakesoul-docker-compose-env_default --rm -t -v ${PWD}/work-dir:/opt/spark/work-dir --env lakesoul_home=/opt/spark/work-dir/lakesoul.properties bitnami/spark:3.3.1 spark-submit --driver-memory 4G --executor-memory 4G --conf spark.driver.memoryOverhead=1500m --conf spark.executor.memoryOverhead=1500m --jars /opt/spark/work-dir/$SPARK_JAR_NAME,/opt/spark/work-dir/mysql-connector-java-8.0.30.jar --class org.apache.spark.sql.lakesoul.benchmark.Benchmark --master local[4] /opt/spark/work-dir/$SPARK_TEST_JAR_NAME
+          docker run --cpus 2 -m 5000m --net lakesoul-docker-compose-env_default --rm -t -v ${PWD}/work-dir:/opt/spark/work-dir --env lakesoul_home=/opt/spark/work-dir/lakesoul.properties bitnami/spark:3.3.1 spark-submit --driver-memory 4G --executor-memory 4G --conf spark.driver.memoryOverhead=1500m --conf spark.executor.memoryOverhead=1500m  --conf spark.dmetasoul.lakesoul.native.io.enable=true --jars /opt/spark/work-dir/$SPARK_JAR_NAME,/opt/spark/work-dir/mysql-connector-java-8.0.30.jar --class org.apache.spark.sql.lakesoul.benchmark.Benchmark --master local[4] /opt/spark/work-dir/$SPARK_TEST_JAR_NAME
diff --git a/lakesoul-spark/src/main/scala/org/apache/spark/sql/lakesoul/sources/LakeSoulSQLConf.scala b/lakesoul-spark/src/main/scala/org/apache/spark/sql/lakesoul/sources/LakeSoulSQLConf.scala
@@ -108,10 +108,10 @@ object LakeSoulSQLConf {
       .createWithDefault(10)
 
   val NATIVE_IO_ENABLE: ConfigEntry[Boolean] =
-    buildConf("native.io.scan.enable")
+    buildConf("native.io.enable")
       .doc(
         """
-           |If ture, org.apache.spark.sql.execution.datasources.parquet.NativeVectorizedReader will be used instead of org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader
+           |If ture, NativeIO would be enabled for both read and write
         """.stripMargin)
       .booleanConf
       .createWithDefault(false)
@@ -142,7 +142,7 @@ object LakeSoulSQLConf {
           |If NATIVE_IO_ENABLE=true, tokio::runtime::Runtime will be build with NATIVE_IO_THREAD_NUM thread_num
         """.stripMargin)
       .intConf
-      .createWithDefault(1)
+      .createWithDefault(2)
 
   val NATIVE_IO_READER_AWAIT_TIMEOUT: ConfigEntry[Int] =
     buildConf("native.io.await.timeout")
@@ -151,5 +151,5 @@ object LakeSoulSQLConf {
           |If NATIVE_IO_ENABLE=true, timeout for each iterate will be set to NATIVE_IO_READER_AWAIT_TIMEOUT mills
         """.stripMargin)
       .intConf
-      .createWithDefault(3000)
+      .createWithDefault(10000)
 }
diff --git a/lakesoul-spark/src/test/scala/org/apache/spark/sql/lakesoul/benchmark/Benchmark.scala b/lakesoul-spark/src/test/scala/org/apache/spark/sql/lakesoul/benchmark/Benchmark.scala
@@ -54,7 +54,9 @@ object Benchmark {
       .config("spark.hadoop.fs.s3a.multipart.size", 67108864)
       .config("spark.hadoop.fs.s3a.connection.maximum", 100)
       .config("spark.hadoop.fs.s3a.endpoint", "http://minio:9000")
-      .config("spark.hadoop.fs.s3a.aws.credentials.provider", "org.apache.hadoop.fs.s3a.AnonymousAWSCredentialsProvider")
+      .config("spark.hadoop.fs.s3a.endpoint.region", "us-east-1")
+      .config("spark.hadoop.fs.s3a.access.key", "minioadmin1")
+      .config("spark.hadoop.fs.s3a.secret.key", "minioadmin1")
       .config("spark.sql.shuffle.partitions", 10)
       .config("spark.sql.files.maxPartitionBytes", "1g")
       .config("spark.default.parallelism", 8)
@@ -67,6 +69,7 @@ object Benchmark {
       .config("spark.sql.catalog.lakesoul", classOf[LakeSoulCatalog].getName)
       .config(SQLConf.DEFAULT_CATALOG.key, LakeSoulCatalog.CATALOG_NAME)
       .config("spark.default.parallelism", "16")
+      .config("spark.dmetasoul.lakesoul.native.io.enable", "true")
 
     val spark = builder.getOrCreate()
     spark.sparkContext.setLogLevel("ERROR")

diff --git a/...park/src/test/scala/org/apache/spark/sql/lakesoul/benchmark/io/ParquetScanBenchmark.scala b/...park/src/test/scala/org/apache/spark/sql/lakesoul/benchmark/io/ParquetScanBenchmark.scala
@@ -40,7 +40,7 @@ object ParquetScanBenchmark {
 
     var bucketName = "lakesoul-test-bucket"
     if (args.length >= 1 && args(0) == "--localtest") {
-      builder.config("spark.hadoop.fs.s3a.endpoint", "http://localhost:9000")
+      builder.config("spark.hadoop.fs.s3a.endpoint", "http://minio:9000")
         .config("spark.hadoop.fs.s3a.endpoint.region", "us-east-1")
         .config("spark.hadoop.fs.s3a.access.key", "minioadmin1")
         .config("spark.hadoop.fs.s3a.secret.key", "minioadmin1")

diff --git a/native-io/lakesoul-io-java/pom.xml b/native-io/lakesoul-io-java/pom.xml
@@ -17,7 +17,7 @@
     <properties>
         <maven.compiler.source>8</maven.compiler.source>
         <maven.compiler.target>8</maven.compiler.target>
-        <arrow.version>11.0.0</arrow.version>
+        <arrow.version>9.0.0</arrow.version>
         <scala.version>2.12.10</scala.version>
         <scala.binary.version>2.12</scala.binary.version>
         <scalatest.version>3.1.0</scalatest.version>

diff --git a/native-io/lakesoul-io/src/lakesoul_reader.rs b/native-io/lakesoul-io/src/lakesoul_reader.rs
@@ -18,15 +18,15 @@ use atomic_refcell::AtomicRefCell;
 use std::mem::MaybeUninit;
 use std::sync::Arc;
 
-use arrow_schema::SchemaRef;
 use arrow::datatypes::Schema;
+use arrow_schema::SchemaRef;
 
 pub use datafusion::arrow::error::ArrowError;
 pub use datafusion::arrow::error::Result as ArrowResult;
 pub use datafusion::arrow::record_batch::RecordBatch;
 pub use datafusion::error::{DataFusionError, Result};
 use datafusion::logical_expr::col as logical_col;
-use datafusion::physical_plan::expressions::{PhysicalSortExpr, col};
+use datafusion::physical_plan::expressions::{col, PhysicalSortExpr};
 
 use datafusion::prelude::SessionContext;
 
@@ -38,12 +38,11 @@ use tokio::runtime::Runtime;
 use tokio::sync::Mutex;
 use tokio::task::JoinHandle;
 
-use crate::lakesoul_io_config::{create_session_context, LakeSoulIOConfig};
-use crate::sorted_merge::sorted_stream_merger::{SortedStream,SortedStreamMerger};
-use crate::sorted_merge::merge_operator::MergeOperator;
 use crate::default_column_stream::default_column_stream::DefaultColumnStream;
 use crate::filter::Parser as FilterParser;
-
+use crate::lakesoul_io_config::{create_session_context, LakeSoulIOConfig};
+use crate::sorted_merge::merge_operator::MergeOperator;
+use crate::sorted_merge::sorted_stream_merger::{SortedStream, SortedStreamMerger};
 
 pub struct LakeSoulReader {
     sess_ctx: SessionContext,
@@ -75,15 +74,21 @@ impl LakeSoulReader {
 
                 let file_schema = Arc::new(Schema::from(df.schema()));
 
-
-                let cols = file_schema.fields().iter().filter(|field| schema.index_of(field.name()).is_ok()).map(|field| logical_col(field.name().as_str())).collect::<Vec<_>>();
+                let cols = file_schema
+                    .fields()
+                    .iter()
+                    .filter(|field| schema.index_of(field.name()).is_ok())
+                    .map(|field| logical_col(field.name().as_str()))
+                    .collect::<Vec<_>>();
 
                 df = df.select(cols)?;
 
-                df = self.config.filter_strs.iter().try_fold(df, |df, f| df.filter(FilterParser::parse(f.clone(), file_schema.clone())))?;
+                df = self.config.filter_strs.iter().try_fold(df, |df, f| {
+                    df.filter(FilterParser::parse(f.clone(), file_schema.clone()))
+                })?;
                 let stream = df.execute_stream().await?;
                 let stream = DefaultColumnStream::new_from_stream(stream, schema.clone());
-                
+
                 self.schema = Some(stream.schema().clone().into());
                 self.stream = Box::new(MaybeUninit::new(Box::pin(stream)));
                 Ok(())
@@ -102,15 +107,18 @@ impl LakeSoulReader {
                         .await?;
 
                     let file_schema = Arc::new(Schema::from(df.schema()));
-                    let cols = file_schema.fields().iter().filter(|field| schema.index_of(field.name()).is_ok()).map(|field| logical_col(field.name().as_str())).collect::<Vec<_>>();
-                    df = df.select(cols)?;   
-                    df = self.config.filter_strs.iter().try_fold(df, |df, f| df.filter(FilterParser::parse(f.clone(), file_schema.clone())))?;
-                    let stream = df
-                        .execute_stream()
-                        .await?;
-                    streams.push(SortedStream::new(
-                        stream,
-                    ));
+                    let cols = file_schema
+                        .fields()
+                        .iter()
+                        .filter(|field| schema.index_of(field.name()).is_ok())
+                        .map(|field| logical_col(field.name().as_str()))
+                        .collect::<Vec<_>>();
+                    df = df.select(cols)?;
+                    df = self.config.filter_strs.iter().try_fold(df, |df, f| {
+                        df.filter(FilterParser::parse(f.clone(), file_schema.clone()))
+                    })?;
+                    let stream = df.execute_stream().await?;
+                    streams.push(SortedStream::new(stream));
                 }
 
                 let mut sort_exprs = Vec::with_capacity(self.config.primary_keys.len());
@@ -121,7 +129,21 @@ impl LakeSoulReader {
                     });
                 }
 
-                let merge_ops = self.config.schema.0.fields().iter().map(|field| MergeOperator::from_name(self.config.merge_operators.get(field.name()).unwrap_or(&String::from("UseLast")))).collect::<Vec<_>>();
+                let merge_ops = self
+                    .config
+                    .schema
+                    .0
+                    .fields()
+                    .iter()
+                    .map(|field| {
+                        MergeOperator::from_name(
+                            self.config
+                                .merge_operators
+                                .get(field.name())
+                                .unwrap_or(&String::from("UseLast")),
+                        )
+                    })
+                    .collect::<Vec<_>>();
 
                 let merge_stream = SortedStreamMerger::new_from_streams(
                     streams,
@@ -202,11 +224,11 @@ impl SyncSendableMutableLakeSoulReader {
 #[cfg(test)]
 mod tests {
     use super::*;
+    use rand::prelude::*;
     use std::mem::ManuallyDrop;
     use std::sync::mpsc::sync_channel;
     use std::time::Instant;
     use tokio::runtime::Builder;
-    use rand::prelude::*;
 
     use arrow::datatypes::{DataType, Field, Schema};
     use arrow::util::pretty::print_batches;

diff --git a/native-io/lakesoul-io/src/lakesoul_writer.rs b/native-io/lakesoul-io/src/lakesoul_writer.rs
@@ -262,7 +262,6 @@ impl MultiPartAsyncWriter {
 impl AsyncBatchWriter for MultiPartAsyncWriter {
     async fn write_record_batch(&mut self, batch: RecordBatch) -> Result<()> {
         let batch = uniform_record_batch(batch);
-        println!{"{:?}", batch.schema()};
         MultiPartAsyncWriter::write_batch(batch, &mut self.arrow_writer, &mut self.in_mem_buf, &mut self.writer).await
     }