這篇文章主要介紹“spark讀取hbase的數(shù)據(jù)實(shí)例代碼”,在日常操作中,相信很多人在spark讀取hbase的數(shù)據(jù)實(shí)例代碼問(wèn)題上存在疑惑,小編查閱了各式資料,整理出簡(jiǎn)單好用的操作方法,希望對(duì)大家解答”spark讀取hbase的數(shù)據(jù)實(shí)例代碼”的疑惑有所幫助!接下來(lái),請(qǐng)跟著小編一起來(lái)學(xué)習(xí)吧!
成都創(chuàng)新互聯(lián)公司專注于黃山企業(yè)網(wǎng)站建設(shè),成都響應(yīng)式網(wǎng)站建設(shè)公司,成都做商城網(wǎng)站。黃山網(wǎng)站建設(shè)公司,為黃山等地區(qū)提供建站服務(wù)。全流程定制網(wǎng)站制作,專業(yè)設(shè)計(jì),全程項(xiàng)目跟蹤,成都創(chuàng)新互聯(lián)公司專業(yè)和態(tài)度為您提供的服務(wù)package hgs.spark.hbase ///tupian/20230522/52675901 import org.apache.spark.SparkConf import org.apache.spark.SparkContext import org.apache.hadoop.hbase.HBaseConfiguration import org.apache.hadoop.hbase.mapreduce.TableInputFormat import org.apache.hadoop.hbase.client.Scan import org.apache.hadoop.hbase.filter.FilterList import org.apache.hadoop.hbase.filter.FilterList.Operator import org.apache.hadoop.hbase.filter.RowFilter import org.apache.hadoop.hbase.filter.RegexStringComparator import org.apache.hadoop.hbase.filter.CompareFilter.CompareOp import org.apache.hadoop.hbase.protobuf.ProtobufUtil import org.apache.hadoop.hbase.util.Base64 import org.apache.hadoop.hbase.util.Bytes import org.apache.hadoop.hbase.filter.LongComparator object HbaseToSpark { def main(args: Array[String]): Unit = { //System.setProperty("spark.serializer", "org.apache.spark.serializer.KryoSerializer"); val conf = new SparkConf conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer") conf.setMaster("local").setAppName("hbasedata") val context = new SparkContext(conf) //hbase配置 val hconf = new HBaseConfiguration hconf.set("hbase.zookeeper.quorum", "bigdata00:2181,bigdata01:2181,bigdata02:2181") hconf.set("hbase.zookeeper.property.clientPort", "2181") hconf.set(TableInputFormat.INPUT_TABLE, "test") val scan = new Scan //掃描的表rowkey的開(kāi)始和結(jié)束 scan.setStartRow("1991".getBytes) scan.setStopRow("3000".getBytes) //val list = new FilterList(Operator.MUST_PASS_ALL) //val filter1 = new RowFilter(CompareOp.GREATER_OR_EQUAL,new LongComparator(1991)) //val filter2 = new RowFilter(CompareOp.LESS_OR_EQUAL,new RegexStringComparator("3000*")) // list.addFilter(filter1) // list.addFilter(filter2) //scan.setFilter(list) //添加scan hconf.set(TableInputFormat.SCAN, convertScanToString(scan)) val hrdd = context.newAPIHadoopRDD(hconf, classOf[TableInputFormat], classOf[org.apache.hadoop.hbase.io.ImmutableBytesWritable], classOf[org.apache.hadoop.hbase.client.Result]) val resultrdd = hrdd.repartition(2) //打印結(jié)果 resultrdd.foreach{case(_,value)=>{ val key = Bytes.toString(value.getRow) val name = Bytes.toString(value.getValue("cf1".getBytes, "name".getBytes)) val age = Bytes.toString(value.getValue("cf1".getBytes, "age".getBytes)) println("rowkey:"+key+" "+"name:"+name+" "+"age:"+age) } } context.stop() } def convertScanToString(scan: Scan) = { val proto = ProtobufUtil.toScan(scan) Base64.encodeBytes(proto.toByteArray) } }
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