使用spark连接到hbase时出现异常

t0ybt7op  于 2021-06-09  发布在  Hbase
关注(0)|答案(1)|浏览(484)

我正在使用spark连接到hbase。我已经添加了所有的依赖项，但仍然得到了这个例外。请帮助我喜欢我需要添加哪个jar来解决这个问题。

SPARK_MAJOR_VERSION is set to 2, using Spark2
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/hdp/2.6.5.0-292/spark2/jars/slf4j-log4j12                                                                                        -1.7.16.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/hdp/2.6.5.0-292/spark2/jars/slf4j-log4j12                                                                                        -1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/hdp/2.6.5.0-292/spark2/jars/phoenix-4.7.0                                                                                        .2.6.5.0-292-client.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/hdp/2.6.5.0-292/spark2/jars/phoenix-4.7.0                                                                                        .2.6.5.0-292-thin-client.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLeve                                                                                        l(newLevel).
18/09/17 05:34:36 WARN Utils: Service 'SparkUI' could not bind on port 4040. Att                                                                                        empting port 4041.
Spark context Web UI available at http://sandbox-hdp.hortonworks.com:4041
Spark context available as 'sc' (master = local[*], app id = local-1537162476668).
Spark session available as 'spark'.
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 2.3.0.2.6.5.0-292
      /_/

Using Scala version 2.11.8 (OpenJDK 64-Bit Server VM, Java 1.8.0_171)
Type in expressions to have them evaluated.
Type :help for more information.

scala> :paste
// Entering paste mode (ctrl-D to finish)

 import org.apache.spark.sql.{SQLContext, _}
 import org.apache.spark.sql.execution.datasources.hbase._
 import org.apache.spark.{SparkConf, SparkContext}
 import spark.sqlContext.implicits._
 import org.apache.hadoop.hbase.HBaseConfiguration
 import org.apache.hadoop.hbase.client.{ConnectionFactory,HBaseAdmin,HTable,Put,Get}
 import org.apache.hadoop.hbase.util.Bytes
 import org.apache.hadoop.hbase.mapreduce.TableInputFormat
 import org.apache.hadoop.hbase.client.HBaseAdmin
 import org.apache.hadoop.hbase.{HTableDescriptor,HColumnDescriptor}

  def catalog = s"""{
     |"table":{"namespace":"default", "name":"Contacts"},
     |"rowkey":"key",
     |"columns":{
     |"rowkey":{"cf":"rowkey", "col":"key", "type":"string"},
     |"officeAddress":{"cf":"Office", "col":"Address", "type":"string"},
     |"officePhone":{"cf":"Office", "col":"Phone", "type":"string"},
     |"personalName":{"cf":"Personal", "col":"Name", "type":"string"},
     |"personalPhone":{"cf":"Personal", "col":"Phone", "type":"string"}
     |}
 |}""".stripMargin

      def withCatalog(cat: String): DataFrame = {
         spark.sqlContext
         .read
         .options(Map(HBaseTableCatalog.tableCatalog->cat))
         .format("org.apache.spark.sql.execution.datasources.hbase")
         .load()
     }
 val df = withCatalog(catalog)
 df.registerTempTable("contacts")
 val query = spark.sqlContext.sql("select personalName, officeAddress from contacts")
 query.show()   <p>

//正在退出粘贴模式，现在正在解释。

warning: there was one deprecation warning; re-run with -deprecation for details
java.lang.NoClassDefFoundError: org/apache/hadoop/hbase/shaded/protobuf/generated/MasterProtos$MasterService$BlockingInterface
at java.lang.ClassLoader.defineClass1(Native Method)
at java.lang.ClassLoader.defineClass(ClassLoader.java:763)
at java.security.SecureClassLoader.defineClass(SecureClassLoader.java:142)
at java.net.URLClassLoader.defineClass(URLClassLoader.java:467)
at java.net.URLClassLoader.access$100(URLClassLoader.java:73)
at java.net.URLClassLoader$1.run(URLClassLoader.java:368)
at java.net.URLClassLoader$1.run(URLClassLoader.java:362)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:361)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:349)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)

下面是spark jar文件夹中的jar

hbase-0.94.2.jar
hbase-annotations-1.2.0.jar
hbase-client-2.1.0.jar
hbase-common-2.1.0.jar
hbase-hadoop-compat-2.1.0.jar
hbase-hadoop2-compat-2.1.0.jar
hbase-it-1.1.2.2.6.5.0-292.jar
hbase-prefix-tree-1.1.2.2.6.5.0-292.jar
hbase-procedure-1.1.2.2.6.5.0-292.jar
hbase-protocol-2.1.0.jar
hbase-server-2.1.0.jar
hbase-spark-1.2.0-cdh5.8.3.jar
hbase-spark-1.1.2.2.6.5.0-292.jar
hbase-thrift-1.1.2.2.6.5.0-292.jar
hive-hbase-handler-0.12.0-cdh5.1.3.jar
hive-hbase-handler-3.1.0.jar
protobuf-java-3.5.1.jar

请提供我的建议，如我错过了在jars文件夹中添加jar，以便连接到hbase。

Mavenhbasescalaapache-sparkapache-spark-sql

1条答案

按热度按时间
i7uaboj4

i7uaboj41#

似乎您缺少了一个shc核心jar，它用于将hortonworks实现的Dataframe写入hbase。
从hortonworks shc连接器导入包时 import org.apache.spark.sql.execution.datasources.hbase._ 您需要将jar添加到spark应用程序中。
获取shc核心连接器jar的步骤：
首先获取hortonworks spark/hbase connector github存储库的pull，然后 checkout 到环境中使用的hbase和hadoop版本的相应分支，并使用

mvn clean install -DskipTests

在执行上面的命令之后，你的内存中会有一个jar ~/.m2/repository/com/hortonworks/shc/ 将这个jar用于spark应用程序。
您可以将其添加到spark jar文件夹中，也可以在spark submit/spark shell中使用--jars标志传递它
然后使用try来执行您正在尝试运行的代码。
我也遵循了同样的步骤，能够用hcatalog读取hbase。
例子 spark-shell --jars shc-core-1.1.3-2.4-s_2.11.jar ```
SPARK_MAJOR_VERSION is set to 2, using Spark2
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use
setLogLevel(newLevel).
Spark context Web UI available at http://sandbox-hdp.hortonworks.com:4040
Spark context available as 'sc' (master = yarn, app id =
application_1592322799672_0007).
Spark session available as 'spark'.
Welcome to

/ / ___ __/ /
\ / _ / _ `/ __/ '/
// ./_,// //_\ version 2.4.0.7.0.3.0-79
//

Using Scala version 2.11.12 (OpenJDK 64-Bit Server VM, Java 1.8.0_232)
Type in expressions to have them evaluated.
Type :help for more information.

scala> :paste
// Entering paste mode (ctrl-D to finish)

import org.apache.spark.sql.{SQLContext, }
import org.apache.spark.sql.execution.datasources.hbase.
import org.apache.spark.{SparkConf, SparkContext}
import spark.sqlContext.implicits._
import org.apache.hadoop.hbase.HBaseConfiguration
import org.apache.hadoop.hbase.client.{ConnectionFactory,HBaseAdmin,HTable,Put,Get}
import org.apache.hadoop.hbase.util.Bytes
import org.apache.hadoop.hbase.mapreduce.TableInputFormat
import org.apache.hadoop.hbase.client.HBaseAdmin
import org.apache.hadoop.hbase.{HTableDescriptor,HColumnDescriptor}

def catalog = s"""{
|"table":{"namespace":"default", "name":"Contacts"},
|"rowkey":"key",
|"columns":{
|"rowkey":{"cf":"rowkey", "col":"key", "type":"string"},
|"officeAddress":{"cf":"Office", "col":"Address", "type":"string"},
|"officePhone":{"cf":"Office", "col":"Phone", "type":"string"},
|"personalName":{"cf":"Personal", "col":"Name", "type":"string"},
|"personalPhone":{"cf":"Personal", "col":"Phone", "type":"string"}
|}
|}""".stripMargin

  def withCatalog(cat: String): DataFrame = {
     spark.sqlContext
     .read
     .options(Map(HBaseTableCatalog.tableCatalog->cat))
     .format("org.apache.spark.sql.execution.datasources.hbase")
     .load()
 }

val df = withCatalog(catalog)
df.registerTempTable("contacts")
val query = spark.sqlContext.sql("select personalName, officeAddress from contacts")
query.show()

// Exiting paste mode, now interpreting.

warning: there was one deprecation warning; re-run with -deprecation for details
Hive Session ID = 5cc02976-98c4-447f-9ba0-e70c4a3c4ab1
+------------+-------------+
|personalName|officeAddress|
+------------+-------------+
|John Jackson| 40 Ellis St.|
|John Jackson| 40 Ellis St.|
+------------+-------------+

import org.apache.spark.sql.{SQLContext, }
import org.apache.spark.sql.execution.datasources.hbase.
import org.apache.spark.{SparkConf, SparkContext}
import spark.sqlContext.implicits._
import org.apache.hadoop.hbase.HBaseConfiguration
import org.apache.hadoop.hbase.client.{ConnectionFactory, HBaseAdmin, HTable, Put, Get}
import org.apache.hadoop.hbase.util.Bytes
import org.apache.hadoop.hbase.mapreduce.TableInputFormat
import org.apache.hadoop.hbase.client.HBaseAdmin
import org.apache.hadoop.hbase.{HTableDescriptor, HColumnDescriptor}
catalog: String
withCatalog: (cat: String)org.apache.spark.sql.DataFrame
df: org.apache.spark.sql.DataFrame = [rowkey: string, officeAddress: string ... 3 more fields]
query: org.apache.spark.sql.DataFrame = [personalName: string, officeAddress: string]

scala> query.show()
+------------+-------------+
|personalName|officeAddress|
+------------+-------------+
|John Jackson| 40 Ellis St.|
|John Jackson| 40 Ellis St.|
+------------+-------------+

scala>

堆栈版本：

HBase 2.2.0
Hadoop 3.1.1
Spark 2.4.0
Scala 2.11.12

赞(0）分享  回复(0）举报  2021-06-09
我来回答

相关问题

    查看更多

    热门标签

    更多
    JavaquerypythonNode开发语言requestUtil数据库Table后端算法LoggerMessageElementParser

    最新问答

    更多
    • 蜀ICP备13028337号-1 大数据知识库 https://www.saoniuhuo.com © All rights reserved
    • 本站内容来源互联网,如果侵犯您的权益请联系我们删除, 联系方式：448109455@qq.com