Drug discovery

进入:/home/hadoop/app/apache-flume-1.6.0-cdh5.7.0-bin/conf新建文件夹并修改它[hadoop@hadoop000 conf]$ vi flume_push_streaming.conf# exec-memory-avro.confsimple-agent.sources = netcat-sourcesimple-agent.sinks = avro-sinksimple-agent.channels = memory-channel.

定时的进行一个时间段内的数据处理Spark Streaming also provides windowed computations, which allow you to apply transformations over a sliding window of data. The following figure illustrates this sliding window.As shown in the figure, every time the window slides over a

Design Patterns for using foreachRDDdstream.foreachRDD is a powerful primitive that allows data to be sent out to external systems.Often writing data to external system requires creating a connection object (e.g. TCP connection to a remote server) and us

Similar to that of RDDs, transformations allow the data from the input DStream to be modified. DStreams support many of the transformations available on normal Spark RDD’s. Some of the common ones are as follows.TransformationMeaningmap(func)Re

Input DStreams are DStreams representing the stream of input data received from streaming sources. In the quick example, lines was an input DStream as it represented the stream of data received from the netcat server. Every input DStream is associated with

Discretized Stream or DStream is the basic abstraction provided by Spark Streaming. It represents a continuous stream of data(连续的数据流), either the input data stream received from source(从源接收到的数据流), or the processed data stream generated by transforming the

Initializing StreamingContextTo initialize a Spark Streaming program, a StreamingContext object has to be created which is the main entry point of all Spark Streaming functionality.A StreamingContext object can be created from a SparkConf object.val con

工作原理:粗粒度Spark St reaming接收到实时数据流，把数据按照指定的时间段切成片片小的数 据块，然后把小的数据块传给Spark Engine处理。

spark-submit的使用使用spark-submit来提交我们的Spark应用程序的脚本(生产):先启动端口9999[hadoop@hadoop000 ~]$ nc -lk 9999然后再[hadoop@hadoop000 bin]下运行以下代码./spark-submit --master local[2] \--class org.apache.spark.examples.streaming.NetworkWordCount \--name NetworkWordCount \

Spark Streaming个人的定义:将不同的数据源的数据经过Spark St reaming处理之后将结果输出到外部文件系统特点:低延时能从错误中高效的恢复: fault-tolerant能够运行在成百上千的节点能够将批处理、机器学习、图计算等子框架和Spark St reaming综合起来使用Spark Streaming receives live input data streams and divides the data into batches, which are the