我正在从Cassandra数据库批量阅读数据,也在使用Scala Spark API从Azure EventHubs流式读取数据。
session.read
.format("org.apache.spark.sql.cassandra")
.option("keyspace", keyspace)
.option("table", table)
.option("pushdown", pushdown)
.load()
&
session.readStream
.format("eventhubs")
.options(eventHubsConf.toMap)
.load()
一切都运行良好,但现在我得到了这个例外frow无处...
User class threw exception: java.lang.NoSuchMethodError: org.apache.spark.sql.catalyst.catalog.SessionCatalog.<init>(Lscala/Function0;Lscala/Function0;Lorg/apache/spark/sql/catalyst/analysis/FunctionRegistry;Lorg/apache/spark/sql/internal/SQLConf;Lorg/apache/hadoop/conf/Configuration;Lorg/apache/spark/sql/catalyst/parser/ParserInterface;Lorg/apache/spark/sql/catalyst/catalog/FunctionResourceLoader;)V
at org.apache.spark.sql.internal.BaseSessionStateBuilder.catalog$lzycompute(BaseSessionStateBuilder.scala:132)
at org.apache.spark.sql.internal.BaseSessionStateBuilder.catalog(BaseSessionStateBuilder.scala:131)
at org.apache.spark.sql.internal.BaseSessionStateBuilder$$anon$1.<init>(BaseSessionStateBuilder.scala:157)
at org.apache.spark.sql.internal.BaseSessionStateBuilder.analyzer(BaseSessionStateBuilder.scala:157)
at org.apache.spark.sql.internal.BaseSessionStateBuilder$$anonfun$build$2.apply(BaseSessionStateBuilder.scala:293)
at org.apache.spark.sql.internal.BaseSessionStateBuilder$$anonfun$build$2.apply(BaseSessionStateBuilder.scala:293)
at org.apache.spark.sql.internal.SessionState.analyzer$lzycompute(SessionState.scala:79)
at org.apache.spark.sql.internal.SessionState.analyzer(SessionState.scala:79)
at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:57)
at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:55)
at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:47)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:74)
at org.apache.spark.sql.SparkSession.baseRelationToDataFrame(SparkSession.scala:428)
at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:233)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:227)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:164)
我不知道具体发生了什么变化,但下面是我的依赖项:
ThisBuild / scalaVersion := "2.11.11"
val sparkVersion = "2.4.0"
libraryDependencies ++= Seq(
"org.apache.logging.log4j" % "log4j-core" % "2.11.1",
"org.apache.spark" %% "spark-core" % sparkVersion % "provided",
"org.apache.spark" %% "spark-sql" % sparkVersion % "provided",
"org.apache.spark" %% "spark-hive" % sparkVersion % "provided",
"org.apache.spark" %% "spark-catalyst" % sparkVersion % "provided",
"org.apache.spark" %% "spark-streaming" % sparkVersion % "provided",
"com.microsoft.azure" % "azure-eventhubs-spark_2.11" % "2.3.10",
"com.microsoft.azure" % "azure-eventhubs" % "2.3.0",
"com.datastax.spark" %% "spark-cassandra-connector" % "2.4.1",
"org.scala-lang.modules" %% "scala-java8-compat" % "0.9.0",
"com.twitter" % "jsr166e" % "1.1.0",
"com.holdenkarau" %% "spark-testing-base" % "2.4.0_0.12.0" % Test,
"MrPowers" % "spark-fast-tests" % "0.19.2-s_2.11" % Test
)
有人知道吗?
1条答案
按热度按时间dw1jzc5e1#
提示我其中一个ilbraries是针对Spark的版本编译的,该版本与当前运行时路径上的版本不同。
https://github.com/apache/spark/blob/v2.4.1/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/SessionCatalog.scala#L56-L63
但不是Spark 2.3.0签名。
我的猜测是有一个运行时Spark 2.3.0的地方?也许你正在运行的应用程序使用Spark提交从Spark 2.3.0安装?