新节点的子节点可能不一样rule.applyOrElse(this,identity[BaseType])}// Check if unchanged and then possibly return old copy to avoid gc churn.//再遍历子节点if(thisfastEquals afterRule){// 如果当前节点没有变化,则继续遍历它的子节点mapChildren(_.transformDown(rule))}else{// 如果当前节点发生改...
这里笔者给出一个思路,就是解析Spark SQL计划,根据Spark SQL的join策略匹配条件等,来判断任务中是否使用了低效的Not in Subquery进行预警,然后通知业务方进行修改。同时,我们在实际完成数据的ETL处理等分析时,也要事前避免类似的低性能SQL。
spark.sql.hive.convertMetastoreParquet默认设置是true, 它代表使用spark-sql内置的parquet的reader和writer(即进行反序列化和序列化),它具有更好地性能,如果设置为false,则代表使用 Hive的序列化方式。 但是有时候当其设置为true时,会出现使用hive查询表有数据,而使用spark查询为空的情况. ...
ignoreMissingFiles => throw ecase e @ (_: RuntimeException | _: IOException) if ignoreCorruptFiles => logWarning( s"Skipped the rest of the content in the corrupted file: $currentFile", e) finished = true null } 1. spark.sql.hive.verifyPartitionPath 上面的两个参数在分区表情况下是针对...
SQL在Spark执行要经历以下几步: 用户提交SQL文本 解析器将SQL文本解析成逻辑计划 分析器结合Catalog对逻辑计划做进一步分析,验证表是否存在,操作是否支持等 优化器对分析器分析的逻辑计划做进一步优化,如将过滤逻辑下推到子查询,查询改写,子查询共用等 Planner再将优化后的逻辑计划根据预先设定的映射逻辑转换为物理执行计...
'spark.sql.extensions=org.apache.spark.sql.hudi.HoodieSparkSessionExtension' 23/07/10 16:16:46 WARN Utils: Your hostname, test001 resolves to a loopback address: 127.0.0.1; using 192.168.137.100 instead (on interface eth0) 23/07/10 16:16:46 WARN Utils: Set SPARK_LOCAL_IP if you ...
5.3 登录hue,选择notebook-editor-sparksql,录入sql 5.4 打开yarn页面,可以看到当前有一个spark thrift server 的job。 5.5 执行5.3 的sql,点击5.4 job 右侧的applicationMaster ,进入spark页面,可以看到如下spark job。在stages页面,我们可以看到执行的sql, ...
Skipping the check allows executing UDFs from pre-localized jars in LLAP; if the jars are not pre-localized, the UDFs will simply fail to load. </description> </property>再次登录执行警告就消失了。八、配置Hudi8.1、检阅官方文档重点地方先来看下官方文档getstart首页:我之前装的hadoop环境是2.7版本...
using builtin-java classes where applicable 16/05/16 21:33:56 WARN Utils: Your hostname, ustc resolves to a loopback address: 127.0.1.1; using 192.168.102.77 instead (on interface eth0) 16/05/16 21:33:56 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address 16/05...
In Spark SQL you can see the type of join being performed by calling queryExecution.executedPlan. As with core Spark, if one of the tables is much smaller than the other you may want a broadcast hash join. You can hint to Spark SQL that a given DF should be broadcast for join by ca...