Question

我有一个将Pyspark流数据转换为数据帧的代码。我需要将此数据帧存储到Hbase中。帮助我另外编写代码。

import sys
from pyspark import SparkContext
from pyspark.streaming import StreamingContext
from pyspark.sql import Row, SparkSession

def getSparkSessionInstance(sparkConf):
if ('sparkSessionSingletonInstance' not in globals()):
    globals()['sparkSessionSingletonInstance'] = SparkSession\
        .builder\
        .config(conf=sparkConf)\
        .getOrCreate()
return globals()['sparkSessionSingletonInstance']


if __name__ == "__main__":
if len(sys.argv) != 3:
    print("Usage: sql_network_wordcount.py <hostname> <port> ", 
file=sys.stderr)
    exit(-1)
host, port = sys.argv[1:]
sc = SparkContext(appName="PythonSqlNetworkWordCount")
ssc = StreamingContext(sc, 1)
lines = ssc.socketTextStream(host, int(port))

def process(time, rdd):
    print("========= %s =========" % str(time))

    try:
        words = rdd.map(lambda line :line.split(" ")).collect()
        spark = getSparkSessionInstance(rdd.context.getConf())
        linesDataFrame = spark.createDataFrame(words,schema=["lat","lon"])

        linesDataFrame.show()
except :
pass

lines.foreachRDD(process)
ssc.start()
ssc.awaitTermination()

Answer 1

您可以使用Spark-Hbase连接器从Spark访问HBase。它在低级RDD和Dataframes中都提供了API。

连接器要求您为HBase表定义Schema。以下是为名称为table1，行键为键和列数（col1-col8）的HBase表定义的架构示例。请注意，rowkey也必须详细定义为具有特定cf（行键）的列（col0）。

def catalog = '{
        "table":{"namespace":"default", "name":"table1"},\
        "rowkey":"key",\
        "columns":{\
          "col0":{"cf":"rowkey", "col":"key", "type":"string"},\
          "col1":{"cf":"cf1", "col":"col1", "type":"boolean"},\
          "col2":{"cf":"cf1", "col":"col2", "type":"double"},\
          "col3":{"cf":"cf1", "col":"col3", "type":"float"},\
          "col4":{"cf":"cf1", "col":"col4", "type":"int"},\
          "col5":{"cf":"cf2", "col":"col5", "type":"bigint"},\
          "col6":{"cf":"cf2", "col":"col6", "type":"smallint"},\
          "col7":{"cf":"cf2", "col":"col7", "type":"string"},\
          "col8":{"cf":"cf2", "col":"col8", "type":"tinyint"}\
        }\
      }'

一旦根据数据框的架构定义了目录，就可以使用以下命令将数据框写入HBase：

df.write\
.options(catalog=catalog)\
.format("org.apache.spark.sql.execution.datasources.hbase")\
.save()

要从HBase读取数据：

df = spark.\
read.\
format("org.apache.spark.sql.execution.datasources.hbase").\
option(catalog=catalog).\
load()

提交Spark应用程序时，您需要包括以下Spark-HBase连接器软件包。

pyspark --packages com.hortonworks:shc-core:1.1.1-2.1-s_2.11 --repositories http://repo.hortonworks.com/content/groups/public/

如何将Pyspark数据帧存储到HBase中

1 个答案: