排查过程：在EMR集群上按小时跑的spark sql 任务有时会失败，在driver端的日志中可以看到报错： org.apache.spark.sql.catalyst.errors.package$TreeNodeException...图片查看错误栈对应的代码 org.apache.spark.sql.execution.exchange.BroadcastExchangeExec....org.apache.spark.sql.execution.exchange.BroadcastExchangeExec....$anonfun$relationFuture$1(BroadcastExchangeExec.scala:169)at org.apache.spark.sql.execution.SQLExecution.../spark/blob/branch-3.0/sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/BroadcastExchangeExec.scala
1.自从spark2.0.0发布没有assembly的包了，在jars里面，是很多小jar包 修改目录查找jar 2.异常HiveConf of name hive.enable.spark.execution.engine...spark task, with exception 'org.apache.hadoop.hive.ql.metadata.HiveException(Failed to create spark client...FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.spark.SparkTask Spark与hive...hive与spark版本必须对应着 重新编译完报 Exception in thread "main" java.lang.NoClassDefFoundError: org/slf4j/impl/StaticLoggerBinder...运行时的日志，查看加载jar包的地方,添加上述jar 5.异常 java.lang.RuntimeException: org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.security.authorize.AuthorizationException
恭喜老铁，跟我遇到了一样的问题，接下来是解决方法： 遇到的问题： org.apache.spark.sql.AnalysisException: Table or view not found: `traintext...:67) at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:128) at org.apache.spark.sql.catalyst.trees.TreeNode...:67) at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:57) at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed...(QueryExecution.scala:48) at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:63) at org.apache.spark.sql.SparkSession.sql...:212) at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126) at org.apache.spark.deploy.SparkSubmit.main
/ slaves 五 ：编写脚本 一 ：基础环境配置 本部分具体步骤可以参考Hadoop集群搭建中的前半部分关于Linux环境搭建以及系统环境配置 二 ：安装包下载 下载链接 ：http://spark.apache.org...thread “main” java.lang.NoClassDefFoundError: org/apache/hadoop/fs/ FSDataInputStream 解决方式 ： 1 ：将master...instantiating ‘org.apache.spark.sql.hive.HiveSessionState’: Caused by: java.lang.RuntimeException: java.net.ConnectException...connection exception: java.net.ConnectException: Connection refused; For more details see: http://wiki.apache.org...>:14: error: not found: value spark import spark.sql ^ 解决思路： 1：定位问题，第一段提示初始化hivesessinstate异常 2：从hadoop01
spark task, with exception 'org.apache.hadoop.hive.ql.metadata.HiveException(Failed to create spark...FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.spark.SparkTask Spark与hive...hive与spark版本必须对应着 重新编译完报 Exception in thread "main" java.lang.NoClassDefFoundError: org/slf4j/impl/...运行时的日志，查看加载jar包的地方,添加上述jar 5.异常 java.lang.RuntimeException: org.apache.hadoop.ipc.RemoteException(...org.apache.hadoop.security.authorize.AuthorizationException): User: root is not allowed to impersonate
CREATE EXTERNAL TABLE my_external_table ( column1 INT, column2 STRING)LOCATION '/path/to/external/data...: org/apache/commons/httpclient/HttpConnection Managerat org.apache.hadoop.hive.ql.exec.mr.ExecMapper.map...(UserGroupInformation.java:1844) at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:169)Caused...by: java.lang.NoClassDefFoundError: org/apache/commons/httpclient/HttpConnectionManagerat org.elasticsearch.hadoop.rest.commonshttp.CommonsHttpTransportFactory.create...数据仓库集成：Hive 是一种常用的数据仓库工具，可以与其他数据仓库组件（如 Hadoop、Spark 等）进行集成。
2.2.0的代码样例： package xingoo.ml.features.tranformer import org.apache.spark.sql.SparkSession import org.apache.spark.ml.feature.StringIndexer...import org.apache.spark.ml.feature....{IndexToString, StringIndexer} import org.apache.spark.sql.SparkSession object IndexToString2 { def...{IndexToString, StringIndexer} import org.apache.spark.sql.SparkSession object IndexToString3 { def...at org.apache.spark.sql.types.StructType$$anonfun$apply$1.apply(StructType.scala:266) at org.apache.spark.sql.types.StructType
首先我们使用新的API方法连接mysql加载数据 创建DF import org.apache.spark.sql.DataFrame import org.apache.spark....{SparkContext, SparkConf} import org.apache.spark.sql....= s""" CREATE TEMPORARY TABLE CI_MDA_SYS_TABLE_COLUMN USING org.apache.spark.sql.jdbc...org.apache.spark.sql.DataFrame.showString(DataFrame.scala:176) at org.apache.spark.sql.DataFrame.show...:193) at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:112) at org.apache.spark.deploy.SparkSubmit.main
java.lang.NoClassDefFoundError: org/apache/spark/sql/SparkSession$ 在【pom】中有【scope】的这个子节点，把这个子节点的限制去掉就行...目录 java.lang.NoClassDefFoundError: org/apache/spark/sql/SparkSession$ scope provided的作用 Demo问题： springboot
import org.apache.spark.streaming....import org.apache.spark.streaming....import org.apache.spark.SparkConf import org.apache.spark.streaming.kafka.KafkaUtils import org.apache.spark.streaming..." java.lang.NoClassDefFoundError: org/apache/spark/streaming/kafka/KafkaUtils$ 修改，添加jar包spark-streaming-kafka....jar \ hadoop000:9092 streamingtopic 报错： java.lang.NoClassDefFoundError: org/apache/hadoop/hbase/client
解决方法：正则表达式的字符串太长，复杂度过高，正则匹配要精练，不要枚举式匹配 90、java.lang.StackOverflowError at org.apache.spark.sql.catalyst.trees.CurrentOrigin...$.withOrigin(TreeNode.scala:53) 解决方法：sql语句的where条件过长，字符串栈溢出 91、org.apache.spark.shuffle.MetadataFetchFailedException...解决方法：原因有多种，去hive.log查看日志进一步定位问题 114、Exception in thread "main" java.lang.NoClassDefFoundError: org...yarn相关包，要保持所有节点jar包一致 119、Error: Could not find or load main class org.apache.hive.beeline.BeeLine...-Phive参数 121、User class threw exception: org.apache.spark.sql.AnalysisException: path hdfs://XXXXXX
依赖于Kettle 是因为一些数据处理逻辑Kettle已经有实现(譬如多线程等)，而使用Hive Metastore 则是因为用Hive的人多。...构建CarbonContext 对象 import org.apache.spark.sql.CarbonContext import java.io.File import org.apache.hadoop.hive.conf.HiveConf...如果写入权限不足，load数据的时候，会出现如下的异常： ERROR 05-07 13:42:49,783 - table:williamtable02 column:bkup generate global...: org.apache.spark.sql.catalyst.analysis.NoSuchTableException at org.spark-project.guava.cache.LocalCache...$LocalLoadingCache.apply(LocalCache.java:4898) at org.apache.spark.sql.hive.HiveMetastoreCatalog.lookupRelation
import org.apache.spark.ml.linalg.DenseVector import org.apache.spark.ml.linalg.Vectors import org.apache.spark.ml.param.ParamMap...import org.apache.spark.sql.Dataset import org.apache.spark.sql.Row import org.apache.spark.sql.SparkSession...import org.apache.spark.sql.catalyst.encoders.RowEncoder import org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema...import org.apache.spark.sql.types.StructType import org.apache.spark.ml.Transformer import org.apache.spark.ml.param...Identifiable } import org.apache.spark.sql.{ DataFrame, Dataset } import org.apache.spark.sql.types.StructType
. */ def update(i: Int, value: Any): Unit } 给出一个非类型安全的UDAF实现： import org.apache.spark.sql.expressions.MutableAggregationBuffer...import org.apache.spark.sql.expressions.UserDefinedAggregateFunction import org.apache.spark.sql.types...._ import org.apache.spark.sql.Row import org.apache.spark.sql.SparkSession object UserDefinedUntypedAggregation...isDistinct = false) new TypedColumn[IN, OUT](expr, encoderFor[OUT]) } } 该类的一个实现 // import org.apache.spark.sql.expressions.Aggregator...import org.apache.spark.sql.Encoder import org.apache.spark.sql.Encoders import org.apache.spark.sql.SparkSession
写数据到HBase表完整代码 import org.apache.spark.sql.SparkSession import org.apache.spark.sql.execution.datasources.hbase.HBaseTableCatalog...HBaseTableCatalog.tableCatalog -> Catalog.schema, HBaseTableCatalog.newTable -> "5")) .format("org.apache.spark.sql.execution.datasources.hbase...从HBase表读数据完整代码 import org.apache.spark.sql....{DataFrame, SparkSession} import org.apache.spark.sql.execution.datasources.hbase.HBaseTableCatalog...sqlContext .read .options(Map(HBaseTableCatalog.tableCatalog -> Catalog.schema)) .format("org.apache.spark.sql.execution.datasources.hbase
2.x之后统一的 package com.javaedge.bigdata.chapter04 import org.apache.spark.sql....{SparkConf, SparkContext} import org.apache.spark.sql....具体来说，这行代码使用了SparkSession对象中的implicits属性，该属性返回了一个类型为org.apache.spark.sql.SQLImplicits的实例。..._，则需要手动导入org.apache.spark.sql.Row以及org.apache.spark.sql.functions._等包，并通过调用toDF()方法将RDD转换为DataFrame。...例如，可以使用 col 函数来创建一个 Column 对象，然后在 select 方法中使用该列： import org.apache.spark.sql.functions.col val selected
{Connection, DriverManager, PreparedStatement, ResultSet} import org.apache.spark.SparkConf import org.apache.spark.SparkContext...import org.apache.spark.rdd....import org.apache.hadoop.hbase.HBaseConfiguration import org.apache.hadoop.hbase.client.Put import org.apache.hadoop.hbase.io.ImmutableBytesWritable...import org.apache.spark.rdd.RDD import org.apache.spark....import org.apache.spark.rdd.RDD import org.apache.spark.
" %% "spark-core" % "3.0.1" libraryDependencies += "org.apache.spark" %% "spark-sql" % "3.0.1" libraryDependencies...+= "org.apache.spark" %% "spark-catalyst" % "3.0.1" libraryDependencies += "org.apache.spark" %% "spark-streaming...代码案例： package cn.datahub import io.delta.tables.DeltaTable import org.apache.spark.sql.SparkSession...import org.apache.spark.sql.functions.expr object Delta { def main(args: Array[String]): Unit = {...", "org.apache.spark.sql.delta.catalog.DeltaCatalog") .getOrCreate() // create table //
package cn.itcast.spark.ds import org.apache.spark.rdd.RDD import org.apache.spark.sql.types.StructType...import org.apache.spark.sql....[String] = [value: string] scala> scala> dataframe.rdd res0: org.apache.spark.rdd.RDD[org.apache.spark.sql.Row..., path: String): Column import org.apache.spark.sql.functions.get_json_object val df = dataframe...import org.apache.spark.sql.
解决方法：正则表达式的字符串太长，复杂度过高，正则匹配要精练，不要枚举式匹配 90、java.lang.StackOverflowError at org.apache.spark.sql.catalyst.trees.CurrentOrigin...$.withOrigin(TreeNode.scala:53) 解决方法：sql语句的where条件过长，字符串栈溢出 91、org.apache.spark.shuffle.MetadataFetchFailedException...解决方法：原因有多种，去hive.log查看日志进一步定位问题 114、Exception in thread “main” java.lang.NoClassDefFoundError: org/apache...yarn相关包，要保持所有节点jar包一致 119、Error: Could not find or load main class org.apache.hive.beeline.BeeLine 解决方法...参数 121、User class threw exception: org.apache.spark.sql.AnalysisException: path hdfs://XXXXXX already
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