2017-02-26 4 views
0

Spark 2.1.0을 사용 중이고 Cassandra 클러스터를 연결하려고합니다. 나는 최신 스파크 릴을 사용했다. 나는 기본 아래와 같이 기본 구성을 설정 한 :spark 세션을 사용하여 Cassandra 테이블을로드 할 수 없습니다. sparklyr 및 R

# local-only configuration 
    sparklyr.cores.local: !expr parallel::detectCores() 
    spark.sql.shuffle.partitions.local: !expr parallel::detectCores() 

    # cassandra settings 
spark.cassandra.connection.host:<Cassandra IP> 
spark.cassandra.auth.username: <uid> 
spark.cassandra.auth.password:<pass> 

sparklyr.defaultPackages: 
- com.databricks:spark-csv_2.11:1.5.0 
- com.datastax.spark:spark-cassandra-connector_2.11:2.0.0-RC1 
- com.datastax.cassandra:cassandra-driver-core:3.1.4 

항아리는 소스 파일이있는 루트 디렉토리에 있습니다.

다음 작업을 수행했습니다. read 함수를 호출하려고 할 때까지 모든 것이 잘되었다. 항아리 위치를 명시 적으로 설정했습니다.

> library(sparklyr) 
    > config <- spark_config() 
    Warning message: 
    In readLines(input, encoding = "UTF-8") : 
     incomplete final line found on '/home/bsc/BSCAnalytics/config.yml' 
    > config[["sparklyr.jars.default"]] <- c("/home/bsc/BSCAnalytics/cassandra-driver-core-3.1.4.jar") 
    > 
    > sc <- spark_connect(master = "local", version = "2.1.0") 
    Warning message: 
    In readLines(input, encoding = "UTF-8") : 
     incomplete final line found on '/home/bsc/BSCAnalytics/config.yml' 
    > Spark.session <- sparklyr::invoke_static(sc, "org.apache.spark.sql.SparkSession", "builder") %>% sparklyr::invoke("config", "spark.cassandra.connection.host", "<Cassandra IP>") %>% sparklyr::invoke("getOrCreate") 

읽기 함수를 호출하려고하면 런타임이 항아리를 찾을 수 없습니다.

> event_df <- invoke(Spark.session, "read") %>% invoke("format", "org.apache.spark.sql.cassandra") %>% invoke("option", "keyspace", "kps") %>% invoke("option", "table", "tab_event") %>% invoke("load") 
Error: java.lang.ClassNotFoundException: Failed to find data source: org.apache.spark.sql.cassandra. Please find packages at http://spark.apache.org/third-party-projects.html 
    at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:569) 
    at org.apache.spark.sql.execution.datasources.DataSource.providingClass$lzycompute(DataSource.scala:86) 
    at org.apache.spark.sql.execution.datasources.DataSource.providingClass(DataSource.scala:86) 
    at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:325) 
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:152) 
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:125) 
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) 
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) 
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) 
    at java.lang.reflect.Method.invoke(Method.java:498) 
    at sparklyr.Invoke$.invoke(invoke.scala:94) 
    at sparklyr.StreamHandler$.handleMethodCall(stream.scala:89) 
    at sparklyr.StreamHandler$.read(stream.scala:55) 
    at sparklyr.BackendHandler.channelRead0(handler.scala:49) 
    at sparklyr.BackendHandler.channelRead0(handler.scala:14) 
    at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) 
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) 
    at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:102) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) 
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) 
    at io.netty.handler.codec.ByteToMessageDecoder.fireChannelRead(ByteToMessageDecoder.java:293) 
    at io.netty.handler.codec.ByteToMessageDecoder.channelRead(ByteToMessageDecoder.java:267) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) 
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) 
    at io.netty.channel.DefaultChannelPipeline$HeadContext.channelRead(DefaultChannelPipeline.java:1294) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) 
    at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:911) 
    at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131) 
    at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:652) 
    at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:575) 
    at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:489) 
    at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:451) 
    at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:140) 
    at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144) 
    at java.lang.Thread.run(Thread.java:745) 
Caused by: java.lang.ClassNotFoundException: org.apache.spark.sql.cassandra.DefaultSource 
    at java.net.URLClassLoader.findClass(URLClassLoader.java:381) 
    at java.lang.ClassLoader.loadClass(ClassLoader.java:424) 
    at java.lang.ClassLoader.loadClass(ClassLoader.java:357) 
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$25$$anonfun$apply$13.apply(DataSource.scala:554) 
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$25$$anonfun$apply$13.apply(DataSource.scala:554) 
    at scala.util.Try$.apply(Try.scala:192) 
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$25.apply(DataSource.scala:554) 
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$25.apply(DataSource.scala:554) 
    at scala.util.Try.orElse(Try.scala:84) 
    at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:554) 
    ... 39 more 

답변

0

당신이 같은 것을 사용할 수 있습니다 :

library(sparklyr) 

config <- spark_config() 
config[["sparklyr.defaultPackages"]] <- c(
    "datastax:spark-cassandra-connector:2.0.0-RC1-s_2.11") 

sc <- spark_connect(master = "local", version = "1.6.1", config = config) 

df <- sparklyr:::spark_data_read_generic(
    sc, 
    "org.apache.spark.sql.cassandra", 
    "format", list(
    keyspace = "dev", 
    table = "emp" 
)) %>% invoke("load") 

cassandra_tbl <- sparklyr:::spark_partition_register_df(
    sc, 
    df, 
    name = "emp", 
    repartition = 0, 
    memory = FALSE) 

cassandra_tbl 

https://github.com/rstudio/sparklyr/issues/520

+0

안녕 하비에르, 감사 참조 나는 다음과 같은 오류를 목격. 나는 당신의 열람에 대한 세부 사항을 다음과 공유하고 추천을 추구하고 싶습니다 : 우리의 스파크 (2.1) 클러스터는 카산드라가 사용자 ID 및 암호로 보호되어 이 나를 주시기 바랍니다 카산드라 (3.x의) 노드에 위치한 공동되지 않습니다 다음을 숙지하십시오. Spark Cassandra 커넥터 단지는 어디에 배치해야하며 Sparlyr은이를 어떻게 나타낼 것입니까? 그것은 당신이 config 매개 변수를 설정하는 함수에 maven 속성을 전달하는 것 같습니다 우리는 어디에서 클러스터 IP, 사용자 ID 및 암호를 전달합니까? 추가 분석을 위해 냉동 또는 기타 Cassandra 복합 물체를 DF에로드하는 방법은 무엇입니까? – SCB