Spark-寒假-实验6

1、flume安装

　　1）上传压缩包并解压

　　2）文件配置

　　　　flume-env.sh

# If this file is placed at FLUME_CONF_DIR/flume-env.sh, it will be sourced
# during Flume startup.

# Enviroment variables can be set here.

export JAVA_HOME=/opt/java/jdk1.8.0_301
export HADOOP_HOME=/opt/Hadoop/hadoop-2.7.3

　　3）启动测试

2. 使用 Avro 数据源测试 Flume

　　1)在flume安装目录下conf文件夹中创建文件：

　　　　zavro.conf：

a1.sources = r1
a1.sinks = k1
a1.channels = c1

# Describe/configure the source
a1.sources.r1.type = avro
a1.sources.r1.channels = c1
a1.sources.r1.bind = 0.0.0.0
a1.sources.r1.port = 4141

# Describe the sink
a1.sinks.k1.type = logger

# Use a channel which buffers events in memory
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100

# Bind the source and sink to the channel
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

　　2）在flume安装目录下创建helloworld.txt文件：

　　　　helloworld.txt:

helloworld

　　3)运行（右边为第一个终端，左边为第二个终端）：

　　　　在第一个终端下运行：

./bin/flume-ng agent agent -c conf -f ./conf/avro.conf -n a1 -Dflume.root.logger=INFO,console

　　　　在第二个终端下运行:

./bin/flume-ng avro-client -H localhost -p 4141 -F ./helloworld.txt

3. 使用 netcat 数据源测试 Flume

　　1)创建文件

　　　　example.conf:

# example.conf: A single-node Flume configuration

# Name the components on this agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1

# Describe/configure the source
a1.sources.r1.type = netcat
a1.sources.r1.bind = localhost
a1.sources.r1.port = 44444

# Describe the sink
a1.sinks.k1.type = logger

# Use a channel which buffers events in memory
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100

# Bind the source and sink to the channel
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

　　2)运行测试（右边为第一个终端，左边为第二个终端）:

　　　　在第一个终端下运行：

./bin/flume-ng agent --conf ./conf --conf-file ./conf/example.conf --name a1 -Dflume.root.logger=INFO,console

　　　　在第二个终端下运行：

telnet localhost 44444

scala学习

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