Spark_spark参数配置优先级

总结 ：

优先级低-》优先级高

spark-submit 提交的优先级 < scala/java代码中的配置参数 < spark SQL hint

spark submit 中提交参数

#!/usr/bin/env bash

source /home/work/batch_job/product/common/common.sh
spark_version="/home/work/opt/spark"
export SPARK_CONF_DIR=${spark_version}/conf/
spark_shell="/home/opt/spark/spark3-client/bin/spark-shell"
spark_sql="/home/work/opt/spark/spark3-client/bin/spark-sql"
echo ${spark_sql}
echo ${spark_shell}
${spark_shell} --master yarn \
        --queue test \
        --name "evelopment_sun-data-new_spark_shell" \
        --conf "spark.speculation=true" \
        --conf "spark.network.timeout=400s" \
        --conf "spark.executor.cores=2" \
        --conf "spark.executor.memory=4g" \
        --conf "spark.executor.instances=300" \
        --conf "spark.driver.maxResultSize=4g" \
        --conf "spark.sql.shuffle.partitions=800" \
        --conf "spark.driver.extraJavaOptions=-Dfile.encoding=utf-8" \
        --conf "spark.executor.extraJavaOptions=-Dfile.encoding=utf-8" \
        --conf "spark.driver.memory=8g" \
        --conf "spark.sql.autoBroadcastJoinThreshold=-1" \
        --conf "spark.sql.turing.pooledHiveClientEnable=false" \
        --conf "spark.sql.hive.metastore.jars=/home/work/opt/spark/spark3-client/hive_compatibility/*" \
        --conf "spark.driver.extraClassPath=./__spark_libs__/hive-extensions-2.0.0.0-SNAPSHOT.jar:./hive_jar/parquet-hadoop-bundle-1.6.0.jar:/home/work/opt/spark/spark3-client/hive_compatibility/parquet-hadoop-bundle-1.6.0.jar" \
       --conf spark.hadoop.mapreduce.fileoutputcommitter.algorithm.version=2 \
       --conf "spark.sql.legacy.timeParserPolicy=LEGACY" \
       --conf "spark.sql.storeAssignmentPolicy=LEGACY" \
       --conf spark.executor.extraJavaOptions="-XX:+UseG1GC" \
       --jars ./online-spark-1.0-SNAPSHOT.jar

scala/java代码中的配置参数

    val conf = new SparkConf().setAppName(s"production_data-new_UserOverview_${event_day}")
    val spark = SparkSession.builder().config("spark.debug.maxToStringFields", "500").config(conf).getOrCreate()

SQL hint

SELECT /*+ MERGEJOIN(t2) */ * FROM t1 INNER JOIN t2 ON t1.key = t2.key;

Hints - Spark 3.5.0 hints Documentation