├── .DS_Store ├── .gitattributes ├── README.md ├── notes ├── .DS_Store └── flume │ └── flume是什么?.md └── 大数据代码demo大全 ├── .DS_Store ├── 00.javaSE ├── .DS_Store ├── 00.刷csdn访客量 │ └── DemoFour.java ├── 01.Stream流操作 │ ├── 01.创建Stream流 │ │ └── StreamConstrctor.java │ ├── 02.Stream流操作 │ │ └── StreamTest.java │ └── 03.收集Stream流结果 │ │ └── StreamCollector.java ├── 02.optional使用 │ └── OptionalTest.java ├── 03.Sets工具类的常用方法 │ └── SetsTest.java ├── 04.使用Multiset统计一首古诗的文字出现频率 │ └── MultisetTest.java └── 05.Immutable不可变集合用法 │ └── ImmutableTest.java ├── 00.java爬虫 ├── .DS_Store ├── HttpClientTest.java └── pachong │ ├── HttpClientTest.java │ ├── Result.java │ ├── Success.java │ └── User.java ├── 000速查表 ├── Hadoop Shell命令速查表.pdf ├── Hive内置函数速查表.pdf ├── Kettle速查表.pdf └── Spark Transformation和Action算子速查表(1).pdf ├── 01.HDFS ├── .DS_Store ├── 01.HDFS常用API │ ├── HDFSApp_03.java │ ├── Test01.java │ └── pom.xml └── 02.将本地的多个小文件拼接成大文件 │ ├── Test02.java │ └── pom.xml ├── 02.MapReduce ├── .DS_Store ├── 01.WordCount │ └── WordCountApp.java ├── 02.将结果封装到Bean │ ├── FlowBean.java │ ├── FlowCountApp.java │ ├── FlowCountMapper.java │ └── FlowCountReduce.java ├── 03.partition │ ├── Demo06Mapper.java │ ├── Demo06PartitionMain.java │ ├── Demo06Partitioner.java │ └── Demo06Reduce.java ├── 04.同住同行 │ ├── 10011.txt │ ├── 10011需求.txt │ └── 代码 │ │ └── WorkTest │ │ ├── TongXing │ │ ├── TongXingDriver01.java │ │ ├── TongXingDriver02.java │ │ ├── TongXingMapper01.java │ │ ├── TongXingMapper02.java │ │ ├── TongXingReducer01.java │ │ └── TongXingReducer02.java │ │ ├── TongZhuDriver.java │ │ ├── TongZhuMapper.java │ │ └── TongZhuReducer.java ├── 05.reduceJoin │ └── demo05 │ │ ├── ReduceJoinBean.java │ │ ├── ReduceJoinDriver.java │ │ ├── ReduceJoinMapper.java │ │ └── ReduceJoinReudce.java ├── 06.MapJoin │ └── demo07 │ │ ├── MapJoinDriver.java │ │ └── MapJoinMapper.java ├── 07.自定义OutputFormat与InputFormat │ └── 自定义inputFormat&&outputFormat.docx ├── 08.MR使用压缩 │ └── MR使用压缩 │ │ └── tt │ │ ├── WordCountDriver.java │ │ ├── WordCountMap.java │ │ └── WordCountReduce.java └── pom.xml ├── 03.Hive ├── 01.自定义UDF │ ├── Custom_UDF.java │ └── pom.xml └── 02.HiveJDBC使用 │ ├── HiveJdbcTest.java │ └── 驱动 │ ├── hive-denpendencies │ ├── commons-httpclient-3.0.1.jar │ ├── commons-logging-1.1.3.jar │ ├── curator-client-2.6.0.jar │ ├── curator-framework-2.6.0.jar │ ├── hadoop-auth-2.6.0-cdh5.14.0.jar │ ├── hadoop-common-2.6.0-cdh5.14.0.jar │ ├── hive-common-1.1.0-cdh5.14.0.jar │ ├── hive-exec-1.1.0-cdh5.14.0.jar │ ├── hive-jdbc-1.1.0-cdh5.14.0.jar │ ├── hive-metastore-1.1.0-cdh5.14.0.jar │ ├── hive-service-1.1.0-cdh5.14.0.jar │ ├── httpclient-4.2.5.jar │ ├── httpcore-4.2.5.jar │ ├── slf4j-api-1.7.5.jar │ └── zookeeper-3.4.5-cdh5.14.0.jar │ └── mysql-connector-java-5.1.38.jar ├── 04.Zookeeper └── 01.创建一个新节点 │ └── ZookeeperDemo.java ├── 05.HBase ├── 01.常用API操作 │ └── HBaseAPI.java ├── 02.过滤器代码操作 │ └── HBaseFilterAPI.java ├── 03.使用MapReduce读取HBase当中一张表的数据，然后将数据写入到HBase当中的另外一张表 │ └── hbaseandmapreduce │ │ ├── HbaseDriver.java │ │ ├── HbaseMapper.java │ │ └── HbaseReduce.java ├── 04.Hbase写入到HDFS │ └── HBase2HDFS.java ├── 05.将HDFS文本文件转换成HFile,并加载到表中 │ └── BulkLoad.java ├── 06.HDFS2Hbase │ └── HDFS2Hbase.java └── pom.xml ├── 06.Flume └── 01_拦截器 │ ├── flumeinteceptor │ ├── BaseFlumeEtlInterceptor.java │ ├── EtlJsonInterceptor.java │ └── MainFlumeIntecptor.java │ ├── pom.xml │ └── utils │ └── LogUtils.java ├── 07.sqoop ├── 01_mysql导入到HDFS │ └── mysql-hdfs.txt ├── 02_hive导出到MySQL │ └── hive-mysql.txt └── 03_mysql到hive │ └── mysql-hive.txt ├── 08.scala └── 01_函数式编程(必须掌握) │ └── tt.scala ├── 09.spark ├── 01_读取大量小文件 │ └── Test01.scala ├── 02_spark的JDBC操作 │ ├── 写数据 │ │ └── Test01.scala │ ├── 所需pom依赖.txt │ └── 读数据 │ │ └── MysqlRDD.scala ├── 03_spark对HBASE操作 │ ├── pom文件.txt │ ├── 写数据 │ │ ├── HBaseSpark.scala │ │ └── hbase-site.xml │ └── 读数据 │ │ └── HBaseSpark.scala ├── 04_广播变量 │ └── BroadcastVariablesTest.scala ├── 05_累加器 │ └── AccumulatorTest.scala ├── 06_SparkSQL读取JDBC数据 │ ├── SparkSqlDemo.scala │ └── Test02.scala ├── 07_SparkSQL读取文件 │ └── SparkSQLReadFileDemo.scala ├── 08_SparkSQL的UDTF │ └── day23.zip ├── 09_SparkStreaming集成kafka │ ├── day25.zip │ └── day25 │ │ ├── SparkStreamingDemo2.scala │ │ └── SparkStreamingKafka.scala ├── 10_StructStreaming │ ├── 01_消费指定端口号数据 │ │ └── Test01.scala │ ├── 02_消费JSON数据 │ │ └── Test02.scala │ ├── 03_消费kafka数据 │ │ └── Test03.scala │ ├── 04_消费kafka数据保存到mysql中 │ │ └── StructStreamingConsumerKafka2Mysql.scala │ └── day26.zip └── SparkPom.txt ├── 10.redis ├── 01_Shell命令 │ └── RedisShell命令.docx ├── 02_RedisAPI │ └── RedisApiDemo.java └── RedisAPIpom.txt ├── 11.kafka ├── 01_模拟生产者 │ └── Produce.java ├── 02_模拟生产者自定义分区 │ ├── KafkaCustomPartitioner.java │ └── KafkaProducerDemo.java └── 03_模拟消费者指定分区消费 │ └── Consumer.java ├── 12.shell脚本 ├── cluster.sh ├── dt.sh ├── f1.sh ├── f2.sh ├── kf.sh ├── km.sh ├── lg.sh ├── xcall.sh ├── xsync └── zk.sh └── 13.flink ├── 00_flink_maven依赖.xml ├── 01_source代码 ├── BatchFromCollection.scala ├── BatchFromFile.scala └── BatchFromHDFS.scala ├── 02_transformation ├── AggregateDemo.scala ├── DistinctDemo.scala ├── FilterDemo.scala ├── FlatMapDemo.scala ├── HashPartitionDemo.scala ├── JoinDemo.scala ├── MapDemo.scala ├── RebalanceDemo.scala ├── ReduceDemo.scala ├── ReduceGroupDemo.scala ├── SortPartitionDemo.scala ├── UnionDemo.scala └── mapPartitionDemo.scala ├── 03_sink ├── BatchSinkCollection.scala └── BatchSinkFile.scala ├── 04_广播变量 └── BroadcastVariableDemo.scala ├── 05_累加器 └── AccumulatorDemo.scala ├── 06_分布式缓存 └── BatchDemoDiskCache.scala └── flink全部 ├── batch ├── flink1 │ ├── createbatch │ │ ├── BatchFromCollection.scala │ │ ├── BatchFromFile.scala │ │ └── BatchFromHDFS.scala │ ├── env │ │ └── BatchCollectionEven.scala │ ├── sink │ │ ├── BatchSinkCollection.scala │ │ └── BatchSinkFile.scala │ └── transformation │ │ ├── AggregateDemo.scala │ │ ├── DistinctDemo.scala │ │ ├── FilterDemo.scala │ │ ├── FlatMapDemo.scala │ │ ├── HashPartitionDemo.scala │ │ ├── JoinDemo.scala │ │ ├── MapDemo.scala │ │ ├── RebalanceDemo.scala │ │ ├── ReduceDemo.scala │ │ ├── ReduceGroupDemo.scala │ │ ├── SortPartitionDemo.scala │ │ ├── UnionDemo.scala │ │ └── mapPartitionDemo.scala └── flink2 │ ├── AccumulatorDemo.scala │ ├── BatchDemoDiskCache.scala │ └── BroadcastVariableDemo.scala ├── highlevel └── FlinkEventTimeAPIChkMain.scala ├── stream ├── sink │ ├── DataSink_Mysql.scala │ └── DataSink_kafka.scala ├── source │ ├── FlinkStreamCustomDataSourceDemo.scala │ ├── FlinkStreamFileSource.scala │ ├── FlinkStreamKafkaSource.scala │ ├── FlinkStreamListSourceDemo.scala │ ├── FlinkStreamMysqlSourceDemo.scala │ └── FlinkStreamSocketSource.scala └── transformation │ ├── ConnectDemo.scala │ ├── SplitAndSelectDemo.scala │ └── WordCountDemo.scala ├── table ├── BatchFlinkTableDemo.scala ├── DataStream_DataSetToTable.scala └── StreamFlinkTableDemo.scala ├── watermark └── WaterMarkDemo.scala └── window ├── WindowApply.scala ├── count ├── StreamingCountSlidingWindow.scala └── StreamingCountTumblingWindow.scala └── time ├── 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