我正在尝试创建 hfiles 以批量加载到 Hbase 中,尽管一切看起来都很好,但它仍然不断抛出行键错误。 我正在使用以下代码:
val df = sqlContext.read.format("com.databricks.spark.csv")
.option("header", "true")
.option("inferSchema", "true")
.load("data.csv")
import sqlContext.implicits._
val DF2 = df.filter($"company".isNotNull)
.dropDuplicates(Array("company"))
.sortWithinPartitions("company").sort("company")
val rdd = DF2.flatMap(x => {
val rowKey = Bytes.toBytes(x(0).toString)
for (i <- 0 to cols.length - 1) yield {
val index = x.fieldIndex(new String(cols(i)))
val value = if (x.isNullAt(index)) "".getBytes else x(index).toString.getBytes
(new ImmutableBytesWritable(rowKey), new KeyValue(rowKey, COLUMN_FAMILY, cols(i), value))
}
})
rdd.saveAsNewAPIHadoopFile("HDFS LOcation", classOf[ImmutableBytesWritable], classOf[KeyValue], classOf[HFileOutputFormat2], fconf)
我正在使用以下数据
company,date,open,high,low,close,volume
ABG,01-Jan-2010,11.53,11.53,11.53,11.53,0
ABM,01-Jan-2010,20.66,20.66,20.66,20.66,0
ABR,01-Jan-2010,1.99,1.99,1.99,1.99,0
ABT,01-Jan-2010,53.99,53.99,53.99,53.99,0
ABX,01-Jan-2010,39.38,39.38,39.38,39.38,0
ACC,01-Jan-2010,28.1,28.1,28.1,28.1,0
ACE,01-Jan-2010,50.4,50.4,50.4,50.4,0
ACG,01-Jan-2010,8.25,8.25,8.25,8.25,0
ADC,01-Jan-2010,27.25,27.25,27.25,27.25,0
它抛出错误为
java.io.IOException: Added a key not lexically larger than previous. Current cell = ADC/data:high/1505862570671/Put/vlen=5/seqid=0, lastCell = ADC/data:open/1505862570671/Put/vlen=5/seqid=0
at org.apache.hadoop.hbase.io.hfile.AbstractHFileWriter.checkKey(AbstractHFileWriter.java:204)
at org.apache.hadoop.hbase.io.hfile.HFileWriterV2.append(HFileWriterV2.java:265)
at org.apache.hadoop.hbase.regionserver.StoreFile$Writer.append(StoreFile.java:992)
at org.apache.hadoop.hbase.mapreduce.HFileOutputFormat2$1.write(HFileOutputFormat2.java:199)
我什至尝试对数据进行排序,但仍然抛出错误。
花了几个小时我找到了解决方案,根本原因是列没有排序。
由于 Hfile 需要按字典顺序排序的键值,并且在您的情况下,在编写
HFileOutputFormat2->AbstractHFileWriter
时发现了 Added a key not lexically larger than previous. Current cell
。您已经在行级别应用了排序,一旦您对列进行排序,它也会起作用。
这里的问题有很好的解释为什么-hbase-keyvaluesortreducer-需要对所有keyvalue进行排序。
解决方案:
//sort columns
val cols = companyDs.columns.sorted
//Rest of the code is same
val output = companyDs.rdd.flatMap(x => {
val rowKey = Bytes.toBytes(x(0).toString)
val hkey = new ImmutableBytesWritable(rowKey)
for (i <- 0 to cols.length - 1) yield {
val index = x.fieldIndex(new String(cols(i)))
val value = if (x.isNullAt(index)) "".getBytes else x(index).toString.getBytes
val kv = new KeyValue(rowKey,COLUMN_FAMILY, cols(i).getBytes(),System.currentTimeMillis()+i ,x(i).toString.getBytes())
(hkey,kv)
}
})
output.saveAsNewAPIHadoopFile("<path>"
, classOf[ImmutableBytesWritable], classOf[KeyValue],
classOf[HFileOutputFormat2], config)
另一种情况:插入数据存在重复的row_key