Flume监控Hive日志并上传到HDFS

一、 实时监控单个追加文件

1.需求:实时监控Hive日志,并上传到HDFS
2.实现步骤
(1)上传Hadoop相关jar包到flume/lib目录下
flume相关jar包
https://blog.csdn.net/Dj_hanhan/article/details/110097742
Flume监控Hive日志并上传到HDFS_第1张图片
(2)进入usr/flume/job目录,创建flume-file-hdfs.conf 文件

# Name the components on this agent
a2.sources = r2
a2.sinks = k2
a2.channels = c2

# Describe/configure the source
a2.sources.r2.type = exec
a2.sources.r2.command = tail -F /usr/apache-hive-1.1.0-bin/logs/hive.log  #hive日志目录

# Describe the sink
a2.sinks.k2.type = hdfs
a2.sinks.k2.hdfs.path = hdfs://master:9000/flume/%Y%m%d/%H  #hdfs地址
#上传文件的前缀
a2.sinks.k2.hdfs.filePrefix = logs-
#是否按照时间滚动文件夹
a2.sinks.k2.hdfs.round = true
#多少时间单位创建一个新的文件夹
a2.sinks.k2.hdfs.roundValue = 1
#重新定义时间单位
a2.sinks.k2.hdfs.roundUnit = hour
#是否使用本地时间戳
a2.sinks.k2.hdfs.useLocalTimeStamp = true
#积攒多少个Event才flush到HDFS一次
a2.sinks.k2.hdfs.batchSize = 1000
#设置文件类型,可支持压缩
a2.sinks.k2.hdfs.fileType = DataStream
#多久生成一个新的文件
a2.sinks.k2.hdfs.rollInterval = 30
#设置每个文件的滚动大小
a2.sinks.k2.hdfs.rollSize = 134217700
#文件的滚动与Event数量无关
a2.sinks.k2.hdfs.rollCount = 0

# Use a channel which buffers events in memory
a2.channels.c2.type = memory
a2.channels.c2.capacity = 1000
a2.channels.c2.transactionCapacity = 100

# Bind the source and sink to the channel
a2.sources.r2.channels = c2
a2.sinks.k2.channel = c2

如果没有hive日志,可以修改hive默认日志存放路径。进入hive的conf目录下修改hive-log4j.properties文件

cp hive-log4j.properties.template hive-log4j.properties #复制模板

vi hive-log4j.properties #编辑文件

修改:

# Define some default values that can be overridden by system properties
hive.log.threshold=ALL
hive.root.logger=INFO,DRFA
hive.log.dir=/usr/apache-hive-1.1.0-bin/logs   #log日志路径
hive.log.file=hive.log

(3)进入flume目录并运行Flume

bin/flume-ng agent --conf conf/ --name a2 --conf-file job/flume-file-hdfs.conf

(4)启动Hadoop和hive
在hive里随便查询一下,创个表啥的。

(5)浏览器打开master:50070

Flume监控Hive日志并上传到HDFS_第2张图片

二、实时监控目录下的多个追加文件

1.需求,使用Flume监听整个目录的实时追加文件,并上传至HDFS
(1)创建配置文件 flume-taildir-hdfs.conf

a3.sources = r3
a3.sinks = k3
a3.channels = c3
# Describe/configure the source
a3.sources.r3.type = TAILDIR
a3.sources.r3.positionFile = /usr/flume/tail_dir.json
a3.sources.r3.filegroups = f1
a3.sources.r3.filegroups.f1 = /usr/flume/files/file.* #需要先创建files目录,否则无法读取文件,文件这里是以file为前缀
# Describe the sink
a3.sinks.k3.type = hdfs
a3.sinks.k3.hdfs.path = hdfs://master:9000/flume/upload/%Y%m%d/%H  //hdfs地址
#上传文件的前缀
a3.sinks.k3.hdfs.filePrefix = upload- #是否按照时间滚动文件夹
a3.sinks.k3.hdfs.round = true
#多少时间单位创建一个新的文件夹
a3.sinks.k3.hdfs.roundValue = 1
#重新定义时间单位
a3.sinks.k3.hdfs.roundUnit = hour
#是否使用本地时间戳
a3.sinks.k3.hdfs.useLocalTimeStamp = true
#积攒多少个 Event 才 flush 到 HDFS 一次
a3.sinks.k3.hdfs.batchSize = 100
#设置文件类型,可支持压缩
a3.sinks.k3.hdfs.fileType = DataStream
#多久生成一个新的文件
a3.sinks.k3.hdfs.rollInterval = 60
#设置每个文件的滚动大小大概是 128M
a3.sinks.k3.hdfs.rollSize = 134217700 #文件的滚动与 Event 数量无关
a3.sinks.k3.hdfs.rollCount = 0
# Use a channel which buffers events in memory
a3.channels.c3.type = memory
a3.channels.c3.capacity = 1000
a3.channels.c3.transactionCapacity = 100
# Bind the source and sink to the channel
a3.sources.r3.channels = c3
a3.sinks.k3.channel = c3

(2)创建文件

cd /usr/flume
mkdir files
echo hello >>file1.txt
echo hello >>file2.txt
echo hello >>file1.txt

(3)启动监控文件夹命令

bin/flume-ng agent --conf conf/ --name a3 --conf-file job/flume-taildir-hdfs.conf

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