scala帮我写一段本地运行的bulkload读取JSON并查询表的程序
以下是一段本地运行的Scala程序,用于读取JSON文件并进行BulkLoad和表查询:
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.hbase.HBaseConfiguration
import org.apache.hadoop.hbase.client.{ConnectionFactory, HTable}
import org.apache.hadoop.hbase.io.ImmutableBytesWritable
import org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFiles
import org.apache.hadoop.hbase.mapreduce.bulkload.{HFileOutputFormat2, TableOutputFormat}
import org.apache.hadoop.hbase.util.Bytes
import org.apache.hadoop.io.{LongWritable, Text}
import org.apache.hadoop.mapreduce.Job
import org.apache.hadoop.mapreduce.lib.input.{FileInputFormat, TextInputFormat}
object BulkLoadJSON {
def main(args: Array[String]) {
val conf: Configuration = HBaseConfiguration.create()
conf.set("hbase.zookeeper.quorum", "localhost")
conf.set("hbase.zookeeper.property.clientPort", "2181")
conf.set(TableOutputFormat.OUTPUT_TABLE, "mytable")
val job: Job = Job.getInstance(conf, "BulkLoadJSON")
job.setJarByClass(this.getClass)
job.setInputFormatClass(classOf[TextInputFormat])
job.setOutputFormatClass(classOf[HFileOutputFormat2])
job.setMapperClass(classOf[JSONMapper])
job.setMapOutputKeyClass(classOf[ImmutableBytesWritable])
job.setMapOutputValueClass(classOf[KeyValueWritable])
FileInputFormat.addInputPath(job, new Path("/path/to/json/file"))
HFileOutputFormat2.setOutputPath(job, new Path("/path/to/hfile/output"))
val table: HTable = new HTable(conf, "mytable")
val bulkLoader: LoadIncrementalHFiles = new LoadIncrementalHFiles(conf)
bulkLoader.doBulkLoad(new Path("/path/to/hfile/output"), table)
// Query table
val rowKey = "rowKey"
val get = new Get(Bytes.toBytes(rowKey))
val result = table.get(get)
val value = Bytes.toString(result.getValue(Bytes.toBytes("cf"), Bytes.toBytes("col")))
println(s"Value for row key $rowKey : $value")
}
}
class JSONMapper extends Mapper[LongWritable, Text, ImmutableBytesWritable, KeyValueWritable] {
val cfBytes: Array[Byte] = Bytes.toBytes("cf")
override def map(key: LongWritable, value: Text, context: Mapper[LongWritable, Text, ImmutableBytesWritable, KeyValueWritable]#Context): Unit = {
// Parse JSON and extract row key and column values
val json = value.toString
val rowKey = extractRowKey(json)
val colValue = extractColValue(json)
// Convert to HBase format and write to context
val rowKeyBytes = Bytes.toBytes(rowKey)
val colValueBytes = Bytes.toBytes(colValue)
val kv = new KeyValueWritable(rowKeyBytes, cfBytes, Bytes.toBytes("col"), colValueBytes)
context.write(new ImmutableBytesWritable(rowKeyBytes), kv)
}
def extractRowKey(json: String): String = ???
def extractColValue(json: String): String = ???
}
class KeyValueWritable(rowKey: Array[Byte], family: Array[Byte], qualifier: Array[Byte], value: Array[Byte]) extends Writable {
override def write(out: DataOutput): Unit = {
out.write(rowKey.length)
out.write(rowKey)
out.write(family.length)
out.write(family)
out.write(qualifier.length)
out.write(qualifier)
out.write(value.length)
out.write(value)
}
override def readFields(in: DataInput): Unit = ???
}
这段程序假定你已经有一个名为mytable的HBase表,并且你要将一个JSON文件加载到该表中。
首先,我们创建一个Configuration对象,并设置Zookeeper连接信息和表名。然后,我们创建一个Job对象和一个HTable对象。
接下来,我们设置输入和输出格式,分别为TextInputFormat和HFileOutputFormat2。我们还设置了JSONMapper作为Mapper类,并设置了输出键和值的类。
在map方法中,我们解析JSON并提取行键和列值,然后将它们转换为HBase格式,并写入到上下文中。
然后,我们将输入路径设置为JSON文件的路径,并将输出路径设置为HFile的输出路径。我们使用LoadIncrementalHFiles实例将HFile加载到HBase表中。
最后,我们查询表以确保数据已成功加载。我们使用Get对象获取行键为rowKey的行,并输出该行的“col”列的值。
请注意,JSONMapper和KeyValueWritable类需要进一步实现,以适应你的JSON格式和表结构。
原文地址: https://www.cveoy.top/t/topic/rqN 著作权归作者所有。请勿转载和采集!