全网第一套PySpark-大数据开发

PySpark-视频[17.08G]

0-导学视频[368.43M]

PySpark导学.mp4[368.43M]

1-第一部分-Spark基础入门[5.04G]

1-第一章[468.88M]

01-课程导入.mp4[5.67M]

Spark基础入门-第一章-1.1-Spark简单介绍.mp4[46.18M]

Spark基础入门-第一章-1.2-Spark风雨十年.mp4[61.13M]

Spark基础入门-第一章-1.3-Spark和Hadoop的对比.mp4[75.02M]

Spark基础入门-第一章-1.4-Spark四大特点.mp4[64.85M]

Spark基础入门-第一章-1.5-Spark框架模块.mp4[57.79M]

Spark基础入门-第一章-1.6-Spark运行模式.mp4[59.03M]

Spark基础入门-第一章-1.7-Spark的架构角色.mp4[88.17M]

Spark基础入门-第一章-总结.mp4[11.04M]

2-第二章[915.76M]

Spark基础入门-第二章-2.1-课程服务器环境.mp4[43.60M]

Spark基础入门-第二章-2.2-Local模式基本原理.mp4[88.65M]

Spark基础入门-第二章-2.3-在Linux上服务器上安装Anaconda.mp4[268.55M]

Spark基础入门-第二章-2.4-SparkLocal模式部署.mp4[514.95M]

3-第三章[1.18G]

Spark基础入门-第三章-3.1-StandAlone的运行原理.mp4[23.39M]

Spark基础入门-第三章-3.2-StandAlone部署.mp4[624.20M]

Spark基础入门-第三章-3.3-StandAlone程序测试.mp4[271.91M]

Spark基础入门-第三章-3.4-Spark程序运行层次划分.mp4[255.49M]

Spark基础入门-第三章-3.5-总结.mp4[34.76M]

4-第四章[344.39M]

Spark基础入门-第四章-4.1-StandAloneHA模式的运行原理.mp4[63.25M]

Spark基础入门-第四章-4.2-StandAlone部署和测试.mp4[251.35M]

Spark基础入门-第四章-4.3-总结.mp4[29.79M]

5-第五章[727.87M]

Spark基础入门-第五章-5.1-SparkOnYARN的运行原理.mp4[90.03M]

Spark基础入门-第五章-5.2-SparkOnYARN部署和测试.mp4[214.69M]

Spark基础入门-第五章-5.3-两种部署模式的区别.mp4[100.92M]

Spark基础入门-第五章-5.4-两种部署模式的演示和总结.mp4[157.93M]

Spark基础入门-第五章-5.5-两种模式任务提交流程.mp4[125.57M]

Spark基础入门-第五章-5.6-总结.mp4[38.74M]

6-第六章[264.20M]

Spark基础入门-第六章-6.1-框架和类库.mp4[42.43M]

Spark基础入门-第六章-6.2-PySpark类库介绍.mp4[56.00M]

Spark基础入门-第六章-6.3-PySpark安装.mp4[156.69M]

Spark基础入门-第六章-6.4-总结.mp4[9.07M]

7-第七章[847.87M]

Spark基础入门-第七章-7.1-本机配置Python环境.mp4[189.34M]

Spark基础入门-第七章-7.2-PyCharm本地和远程解释器配置.mp4[106.98M]

Spark基础入门-第七章-7.3-编程入口SparkContext对象以及WordCount演示.mp4[248.97M]

Spark基础入门-第七章-7.4-WordCount代码流程解析.mp4[134.60M]

Spark基础入门-第七章-7.5-提交WordCount到Linux集群运行.mp4[144.23M]

Spark基础入门-第七章-7.6-总结.mp4[23.75M]

8-第八章[377.13M]

Spark基础入门-第八章-8.1-Spark运行角色回顾.mp4[72.42M]

Spark基础入门-第八章-8.2-分布式代码执行分析.mp4[156.84M]

Spark基础入门-第八章-8.3-PythonOnSpark执行原理.mp4[135.93M]

Spark基础入门-第八章-总结.mp4[11.95M]

2-第二部分-SparkCore[6.00G]

1-第一章[448.63M]

SparkCore-第一章-1.1-什么是RDD.mp4[22.11M]

SparkCore-第一章-1.2-RDD五大特性-特性1.mp4[15.74M]

SparkCore-第一章-1.3-RDD五大特性-特性2.mp4[61.14M]

SparkCore-第一章-1.4-RDD的五大特性-特性3.mp4[26.84M]

SparkCore-第一章-1.5-RDD的五大特性-特性4.mp4[42.87M]

SparkCore-第一章-1.6-RDD的五大特性-特性5.mp4.mp4[53.15M]

SparkCore-第一章-1.7-WordCount结合RDD特性进行执行分析.mp4[205.30M]

SparkCore-第一章-1.8-总结.mp4[21.49M]

2-第二章[2.45G]

SparkCore-第二章-10-RDD算子-filter.mp4[37.06M]

SparkCore-第二章-11-RDD算子-distinct.mp4[53.73M]

SparkCore-第二章-12-RDD算子-union.mp4[31.62M]

SparkCore-第二章-13-RDD算子-join.mp4[86.96M]

SparkCore-第二章-14-RDD算子-intersection.mp4[29.46M]

SparkCore-第二章-15-RDD算子-glom.mp4[9.26M]

SparkCore-第二章-16-RDD算子-groupByKey.mp4[55.64M]

SparkCore-第二章-17-RDD算子-sortBy.mp4[100.83M]

SparkCore-第二章-18-RDD算子-sortByKey.mp4[78.44M]

SparkCore-第二章-19-RDD算子-案例.mp4[146.47M]

SparkCore-第二章-1-RDD的创建-1.mp4[31.39M]

SparkCore-第二章-20-RDD算子-案例-提交到YARN执行.mp4[340.44M]

SparkCore-第二章-21-RDD算子-countByKey.mp4[58.40M]

SparkCore-第二章-22-RDD算子-reduce.mp4[53.11M]

SparkCore-第二章-23-RDD算子-fold.mp4[57.46M]

SparkCore-第二章-24-RDD算子-take-first-count-top.mp4[41.78M]

SparkCore-第二章-25-RDD算子-takeSample.mp4[73.94M]

SparkCore-第二章-26-RDD算子-takeOrdered.mp4[40.16M]

SparkCore-第二章-27-RDD算子-foreach.mp4[72.47M]

SparkCore-第二章-28-RDD算子-saveAsTextFile.mp4[118.39M]

SparkCore-第二章-29-RDD算子-mapPartitions.mp4[86.75M]

SparkCore-第二章-2-RDD的创建-2.mp4[210.02M]

SparkCore-第二章-30-RDD算子-foreachPartition.mp4[37.86M]

SparkCore-第二章-31-RDD算子-partitionBy.mp4[74.59M]

SparkCore-第二章-32-RDD算子-repartition-coalesce.mp4[95.14M]

SparkCore-第二章-33-RDD算子-面试题-groupByKey和reduceByKey的区别.mp4[56.50M]

SparkCore-第二章-34-总结.mp4[10.35M]

SparkCore-第二章-3-RDD算子概念和分类.mp4[67.11M]

SparkCore-第二章-4-转换算子-map.mp4[104.95M]

SparkCore-第二章-5-转换算子-flatMap.mp4[56.42M]

SparkCore-第二章-6-转换算子-reduceByKey.mp4[21.36M]

SparkCore-第二章-7-RDD算子-mapValues.mp4[40.74M]

SparkCore-第二章-8-WordCount案例回顾.mp4[53.72M]

SparkCore-第二章-9-RDD算子-groupBy.mp4[81.39M]

3-第三章[534.37M]

SparkCore-第三章-1-RDD的数据是过程数据概念.mp4[52.26M]

SparkCore-第三章-2-RDD的缓存.mp4[323.24M]

SparkCore-第三章-3-RDD的CheckPoint.mp4[138.09M]

SparkCore-第三章-4-总结.mp4[20.77M]

4-第四章[1.03G]

SparkCore-第四章-1-jieba库入门使用.mp4[146.29M]

SparkCore-第四章-2-案例需求1开发.mp4[373.43M]

SparkCore-第四章-3-案例需求2开发.mp4[227.51M]

SparkCore-第四章-4-案例需求3开发.mp4[140.39M]

SparkCore-第四章-5-提交代码到YARN集群运行.mp4[153.12M]

SparkCore-第四章-6-作业和总结.mp4[8.88M]

5-第五章[858.34M]

SparkCore-第五章-1-广播变量.mp4[354.61M]

SparkCore-第五章-2-累加器.mp4[213.12M]

SparkCore-第五章-3-广播变量累加器综合案例.mp4[287.43M]

SparkCore-第五章-4-总结.mp4[3.17M]

6-第六章[736.79M]

SparkCore-第六章-1-DAG.mp4[86.26M]

SparkCore-第六章-2-宽窄依赖和阶段划分.mp4[73.07M]

SparkCore-第六章-3-内存迭代计算.mp4[217.51M]

SparkCore-第六章-4-Spark并行度.mp4[86.48M]

SparkCore-第六章-5-Spark任务调度.mp4[168.34M]

SparkCore-第六章-6-Spark运行概念名词解释和层级梳理.mp4[90.16M]

SparkCore-第六章-7-总结.mp4[14.97M]

3-第三部分-SparkSQL[4.11G]

1-第一章[32.28M]

SparkSQL-第一章-SparkSQL基础入门.mp4[32.28M]

2-第二章[289.00M]

SparkSQL-第二章-1-SparkSQL和Hive的异同以及SparkSQL的数据抽象.mp4[141.30M]

SparkSQL-第二章-2-SparkSession执行环境入口构建和SparkSQLHelloWorld.mp4[142.14M]

SparkSQL-第二章-3-总结.mp4[5.56M]

3-第三章[2.31G]

SparkSQL-第三章-10-DSL风格入门API.mp4[200.05M]

SparkSQL-第三章-11-SQL风格入门API.mp4[73.21M]

SparkSQL-第三章-12-WordCount案例.mp4[216.29M]

SparkSQL-第三章-13-电影评分案例编程.mp4[530.20M]

SparkSQL-第三章-14-SparkSQLShuffle阶段分区数参数设定.mp4[108.97M]

SparkSQL-第三章-15-异常数据处理API.mp4[300.02M]

SparkSQL-第三章-16-DataFrame数据写出.mp4[153.07M]

SparkSQL-第三章-17-DataFrame使用JDBC协议读写数据库(MySQL).mp4[176.64M]

SparkSQL-第三章-18-总结.mp4[9.53M]

SparkSQL-第三章-1-DataFrame对象的构成.mp4[18.96M]

SparkSQL-第三章-2-DataFrame创建-1.mp4[194.59M]

SparkSQL-第三章-3-DataFrame创建-2.mp4[92.99M]

SparkSQL-第三章-4-DataFrame创建-3.mp4[64.56M]

SparkSQL-第三章-5-DataFrame创建-4-基于Pandas的DF转换为SparkSQL的DF对象.mp4[6.96M]

SparkSQL-第三章-6-标准API读取text数据源构建DataFrame.mp4[69.29M]

SparkSQL-第三章-7-标准API读取json构建DataFrame.mp4[32.21M]

SparkSQL-第三章-8-标准API读取jcsv构建DataFrame.mp4[50.80M]

SparkSQL-第三章-9-标准API读取jparquet构建DataFrame.mp4[65.29M]

4-第四章[782.04M]

SparkSQL-第四章-1-UDF创建演示.mp4[228.18M]

SparkSQL-第四章-2-注册返回值是数组类型的UDF.mp4[131.32M]

SparkSQL-第四章-3-返回字典类型的UDF定义.mp4[145.40M]

SparkSQL-第四章-4-拓展-通过RDD代码模拟UDAF效果.mp4[101.60M]

SparkSQL-第四章-5-窗口函数的演示.mp4[170.80M]

SparkSQL-第四章-6-总结.mp4[4.74M]

5-第五章[96.82M]

SparkSQL-第五章-1-Catalyst优化器.mp4[54.68M]

SparkSQL-第五章-2-SparkSQL执行流程及本章总结.mp4[42.14M]

6-第六章[334.22M]

SparkSQL-第六章-SparkOnHive原理和配置及总结.mp4[334.22M]

7-第七章[309.39M]

SparkSQL-第七章-分布式SQL的执行引擎原理和配置.mp4[309.39M]

4-第四部分-案例[800.20M]

案例-案例背景及需求1开发.mp4[81.98M]

案例-需求2开发.mp4[411.11M]

案例-需求3开发.mp4[71.42M]

案例-需求4开发.mp4[235.69M]

5-第五部分-Spark新特性及核心回顾[819.51M]

Spark新特性及核心回顾-1-1-HashShuffleManager.mp4[101.99M]

Spark新特性及核心回顾-1-2-SortShuffleManager.mp4[86.46M]

Spark新特性及核心回顾-1-3-总结.mp4[18.48M]

Spark新特性及核心回顾-2-1-3.0新特性-AQE.mp4[176.45M]

Spark新特性及核心回顾-2-2-新特性-动态分区裁剪.mp4[47.10M]

Spark新特性及核心回顾-2-3-新特性-koalas库.mp4[303.84M]

Spark新特性及核心回顾-2-4-总结.mp4[24.25M]

Spark新特性及核心回顾-3-Spark概念总结.mp4[60.94M]

PySpark-资料[91.72G]

PPT[21.00M]

1-Spark基础入门.pdf[5.78M]

2-Spark核心编程.pdf[6.18M]

3-SparkSQL.pdf[6.48M]

4-Spark综合案例.pdf[466.45K]

5-Spark核心回顾+新特性.pdf[2.11M]

PySpark[134.20M]

.idea[247.34K]

dataSources[211.60K]

4cdf66ac-d750-4206-bbeb-8ead556a9987[134.48K]

storage_v2[134.48K]

_src_[134.48K]

schema[134.48K]

information_schema.FNRwLQ.meta[0.02K]

information_schema.FNRwLQ.zip[134.26K]

mysql.osA4Bg.meta[0.06K]

performance_schema.kIw0nw.meta[0.07K]

sys.zb4BAA.meta[0.06K]

d2a6b123-693e-4a50-99c8-2b5a966f72a4[0.27K]

storage_v2[0.27K]

_src_[0.27K]

schema[0.27K]

information_schema.FNRwLQ.meta[0.07K]

mysql.osA4Bg.meta[0.06K]

performance_schema.kIw0nw.meta[0.07K]

sys.zb4BAA.meta[0.06K]

4cdf66ac-d750-4206-bbeb-8ead556a9987.xml[37.77K]

d2a6b123-693e-4a50-99c8-2b5a966f72a4.xml[39.08K]

inspectionProfiles[0.17K]

profiles_settings.xml[0.17K]

.gitignore[0.18K]

dataSources.local.xml[1.81K]

dataSources.xml[0.86K]

deployment.xml[0.53K]

misc.xml[0.26K]

modules.xml[0.27K]

PySpark.iml[0.40K]

workspace.xml[31.27K]

00_example[0.95K]

__init__.py

HelloWorld.py[0.95K]

01_RDD[26.90K]

example[4.09K]

__init__.py

defs.py[1.00K]

jieba_test.py[0.45K]

main.py[2.65K]

__init__.py

01_RDD_create_parallelize.py[0.87K]

02_RDD_create_textFile.py[0.99K]

03_RDD_create_wholeTextFile.py[0.32K]

04_RDD_operators_map.py[0.67K]

05_RDD_operators_flatMap.py[0.50K]

06_RDD_operators_reduceByKey.py[0.38K]

07_RDD_wordcount_example.py[0.76K]

08_RDD_operators_groupBy.py[0.59K]

09_RDD_operators_filter.py[0.35K]

10_RDD_operators_distinct.py[0.42K]

11_RDD_operators_union.py[0.43K]

12_RDD_operators_join.py[0.67K]

13_RDD_operators_intersection.py[0.43K]

14_RDD_operators_glom.py[0.30K]

15_RDD_operators_gorupByKey.py[0.36K]

16_RDD_operators_sortBy.py[0.82K]

17_RDD_operators_sortByKey.py[0.54K]

18_RDD_operators_demo.py[0.96K]

19_defs.py[0.10K]

19_RDD_operators_demo_run_yarn.py[1.57K]

20_RDD_operators_countByKey.py[0.45K]

20_RDD_operators_countByValue.py[0.82K]

21_RDD_operators_reduce.py[0.27K]

22_RDD_operators_fold.py[0.29K]

23_RDD_operators_takeSample.py[0.29K]

24_RDD_operators_takeOrdered.py[0.32K]

25_RDD_operators_foreach.py[0.29K]

26_RDD_operators_saveAsTextFile.py[0.30K]

27_RDD_operators_mapPartitions.py[0.42K]

28_RDD_operators_foreachPartition.py[0.41K]

29_RDD_operators_partitionBy.py[0.53K]

30_RDD_operators_repartition_and_coalesce.py[0.50K]

31_RDD_cache.py[0.68K]

32_RDD_checkpoint.py[0.78K]

33_RDD_broadcast.py[1.57K]

34_RDD_accumulator.py[0.68K]

35_RDD_broadcast_and_accumulator_demo.py[2.08K]

defs_19.py[0.10K]

02_SQL[32.32K]

example[6.24K]

main.py[6.24K]

__init__.py

00_spark_session_create.py[0.80K]

01_dataframe_create_1.py[1.21K]

02_dataframe_create_2.py[0.83K]

03_dataframe_create_3.py[0.87K]

04_dataframe_create_4.py[0.68K]

05_dataframe_create_5_text.py[0.72K]

06_dataframe_create_6_json.py[0.51K]

07_dataframe_create_7_csv.py[0.66K]

08_dataframe_create_8_parquet.py[0.52K]

09_dataframe_process_dsl_helloworld.py[1.55K]

10_dataframe_process_sql_helloworld.py[1.15K]

11_wordcount_demo.py[1.28K]

12_movie_demo.py[3.80K]

13_data_clear_api.py[1.67K]

14_dataframe_write.py[1.64K]

15_dataframe_jdbc.py[1.74K]

16_udf_define.py[1.88K]

17_udf_define_return_array.py[1.16K]

18_udaf_by_rdd.py[1.06K]

18_udf_define_return_dict.py[1.23K]

19_spark_on_hive.py[0.72K]

20_jdbc_spark_thrift_server.py[0.41K]

data[133.89M]

input[123.03M]

sql[1.89M]

hello_world.txt[0.04K]

people.csv[0.18K]

people.json[0.07K]

people.txt[0.03K]

stu_score.avi[1.20K]

stu_score.txt[1.20K]

u.data[1.89M]

user.avsc[0.18K]

users.avro[0.33K]

users.orc[0.53K]

users.parquet[0.60K]

tiny_files[0.19K]

1.txt[0.04K]

2.txt[0.04K]

3.txt[0.04K]

4.txt[0.04K]

5.txt[0.04K]

19_window_function.py[2.06K]

accumulator_broadcast_data.txt[0.21K]

apache.log[1.41K]

mini.json[118.62M]

minimini.json[1.17M]

order.text[2.84K]

SogouQ.txt[1.34M]

stu_info.txt[0.32K]

stu_score.txt[1.20K]

words.txt[0.04K]

output[10.86M]

out1[0.03K]

._SUCCESS.crc[0.01K]

.part-00000.crc[0.01K]

_SUCCESS

part-00000[0.01K]

out2[0.06K]

._SUCCESS.crc[0.01K]

.part-00000.crc[0.01K]

.part-00001.crc[0.01K]

.part-00002.crc[0.01K]

_SUCCESS

part-00000

part-00001

part-00002[0.01K]

sql[10.86M]

csv[1.90M]

._SUCCESS.crc[0.01K]

.part-00000-975c88ec-ebca-4fc7-9a70-d5b9a05939a6-c000.csv.crc[15.11K]

_SUCCESS

part-00000-975c88ec-ebca-4fc7-9a70-d5b9a05939a6-c000.csv[1.89M]

json[5.65M]

._SUCCESS.crc[0.01K]

.part-00000-b1aec1bd-5dad-4bce-b2ff-d725cfefdead-c000.json.crc[44.86K]

_SUCCESS

part-00000-b1aec1bd-5dad-4bce-b2ff-d725cfefdead-c000.json[5.61M]

parquet[849.38K]

._SUCCESS.crc[0.01K]

.part-00000-8f1cc3c0-1134-4752-8ca5-5d09f4f3151c-c000.snappy.parquet.crc[6.59K]

_SUCCESS

part-00000-8f1cc3c0-1134-4752-8ca5-5d09f4f3151c-c000.snappy.parquet[842.78K]

text[2.48M]

._SUCCESS.crc[0.01K]

.part-00000-8da24ab2-229c-4296-b160-43655cb46ffa-c000.txt.crc[19.69K]

_SUCCESS

part-00000-8da24ab2-229c-4296-b160-43655cb46ffa-c000.txt[2.46M]

main.py[0.02K]

test.py[2.77K]

完整虚拟机2021-SZ[89.14G]

大数据环境统一虚拟机[51.63G]

文档[15.23M]

01-安装VMware虚拟机.doc[643.00K]

02-虚拟机安装.doc[2.06M]

03-CRT连接linux.doc[1.15M]

04-vmware软件卸载.doc[579.00K]

05-大数据环境配置统一.doc[3.08M]

06-zookeeper集群安装.doc[178.20K]

07-hadoop集群安装操作.doc[310.98K]

08-hive安装操作.doc[196.53K]

09-spark部署文档.doc[2.41M]

10-HBase安装操作.docx[204.61K]

11-Phoenix的安装操作.doc[409.47K]

12-kafka环境搭建.docx[89.71K]

13-flume安装以及nosql综合案例环境.doc[141.05K]

14-flink集群安装.doc[3.84M]

虚拟机[42.54G]

node1[16.81G]

node1.nvram[8.48K]

node1.vmdk[1.76G]

node1.vmsd[7.69K]

node1.vmx[2.59K]

node1.vmxf[0.25K]

node1-000001.vmdk[482.88M]

node1-000002.vmdk[760.69M]

node1-000003.vmdk[600.94M]

node1-000004.vmdk[82.75M]

node1-000005.vmdk[0.99G]

node1-000006.vmdk[688.19M]

node1-000007.vmdk[491.06M]

node1-000008.vmdk[5.86G]

node1-000009.vmdk[29.38M]

node1-000010.vmdk[27.38M]

node1-000011.vmdk[477.75M]

node1-000012.vmdk[30.25M]

node1-000013.vmdk[831.25M]

node1-000014.vmdk[28.38M]

node1-000015.vmdk[37.56M]

node1-000016.vmdk[492.44M]

node1-000017.vmdk[149.25M]

node1-000018.vmdk[34.75M]

node1-000019.vmdk[212.44M]

node1-000020.vmdk[780.00M]

node1-000021.vmdk[644.94M]

node1-000022.vmdk[1.46G]

node1-000023.vmdk[12.56M]

node1-Snapshot1.vmsn[27.39K]

node1-Snapshot10.vmsn[27.40K]

node1-Snapshot11.vmsn[27.40K]

node1-Snapshot12.vmsn[27.40K]

node1-Snapshot13.vmsn[27.40K]

node1-Snapshot14.vmsn[27.43K]

node1-Snapshot15.vmsn[27.43K]

node1-Snapshot16.vmsn[27.43K]

node1-Snapshot17.vmsn[27.43K]

node1-Snapshot18.vmsn[27.43K]

node1-Snapshot19.vmsn[27.43K]

node1-Snapshot2.vmsn[27.40K]

node1-Snapshot20.vmsn[27.43K]

node1-Snapshot21.vmsn[27.43K]

node1-Snapshot22.vmsn[27.43K]

node1-Snapshot23.vmsn[27.43K]

node1-Snapshot3.vmsn[27.40K]

node1-Snapshot4.vmsn[27.40K]

node1-Snapshot5.vmsn[27.40K]

node1-Snapshot6.vmsn[27.40K]

node1-Snapshot7.vmsn[27.40K]

node1-Snapshot8.vmsn[27.40K]

node1-Snapshot9.vmsn[27.40K]

vmware.log[179.14K]

vmware-0.log[180.84K]

vmware-1.log[184.27K]

vmware-2.log[177.89K]

node2[13.47G]

node1-cl1.vmdk[1.76G]

node1-cl1-000001.vmdk[418.25M]

node1-cl1-000002.vmdk[69.13M]

node1-cl1-000003.vmdk[588.94M]

node1-cl1-000004.vmdk[341.06M]

node1-cl1-000005.vmdk[22.88M]

node1-cl1-000006.vmdk[5.97G]

node1-cl1-000007.vmdk[279.75M]

node1-cl1-000008.vmdk[25.44M]

node1-cl1-000009.vmdk[477.63M]

node1-cl1-000010.vmdk[26.94M]

node1-cl1-000011.vmdk[583.06M]

node1-cl1-000012.vmdk[26.31M]

node1-cl1-000013.vmdk[27.63M]

node1-cl1-000014.vmdk[92.06M]

node1-cl1-000015.vmdk[90.94M]

node1-cl1-000016.vmdk[322.19M]

node1-cl1-000017.vmdk[24.19M]

node1-cl1-000018.vmdk[24.06M]

node1-cl1-000019.vmdk[962.31M]

node1-cl1-000020.vmdk[1.43G]

node1-cl1-000021.vmdk[12.56M]

node2.nvram[8.48K]

node2.vmsd[7.15K]

node2.vmx[2.58K]

node2.vmxf[0.25K]

node2-Snapshot1.vmsn[27.38K]

node2-Snapshot10.vmsn[27.41K]

node2-Snapshot11.vmsn[27.41K]

node2-Snapshot12.vmsn[27.41K]

node2-Snapshot13.vmsn[27.41K]

node2-Snapshot14.vmsn[27.42K]

node2-Snapshot15.vmsn[27.42K]

node2-Snapshot16.vmsn[27.42K]

node2-Snapshot17.vmsn[27.42K]

node2-Snapshot18.vmsn[27.42K]

node2-Snapshot19.vmsn[27.42K]

node2-Snapshot2.vmsn[27.39K]

node2-Snapshot20.vmsn[27.42K]

node2-Snapshot21.vmsn[27.42K]

node2-Snapshot3.vmsn[27.39K]

node2-Snapshot4.vmsn[27.41K]

node2-Snapshot5.vmsn[27.42K]

node2-Snapshot6.vmsn[27.42K]

node2-Snapshot7.vmsn[27.42K]

node2-Snapshot8.vmsn[27.42K]

node2-Snapshot9.vmsn[27.41K]

vmware.log[177.58K]

vmware-0.log[177.99K]

vmware-1.log[181.32K]

vmware-2.log[176.29K]

node3[12.26G]

node1-cl1.vmdk[1.76G]

node1-cl1-000001.vmdk[418.25M]

node1-cl1-000002.vmdk[68.75M]

node1-cl1-000003.vmdk[588.19M]

node1-cl1-000004.vmdk[339.81M]

node1-cl1-000005.vmdk[22.88M]

node1-cl1-000006.vmdk[277.94M]

node1-cl1-000007.vmdk[5.97G]

node1-cl1-000008.vmdk[25.38M]

node1-cl1-000009.vmdk[255.06M]

node1-cl1-000010.vmdk[25.88M]

node1-cl1-000011.vmdk[576.00M]

node1-cl1-000012.vmdk[25.94M]

node1-cl1-000013.vmdk[27.81M]

node1-cl1-000014.vmdk[90.81M]

node1-cl1-000015.vmdk[100.75M]

node1-cl1-000016.vmdk[24.25M]

node1-cl1-000017.vmdk[24.13M]

node1-cl1-000018.vmdk[23.75M]

node1-cl1-000019.vmdk[962.75M]

node1-cl1-000020.vmdk[757.63M]

node1-cl1-000021.vmdk[12.56M]

node3.nvram[8.48K]

node3.vmsd[7.16K]

node3.vmx[2.58K]

node3.vmxf[0.25K]

node3-Snapshot1.vmsn[27.38K]

node3-Snapshot10.vmsn[27.41K]

node3-Snapshot11.vmsn[27.41K]

node3-Snapshot12.vmsn[27.41K]

node3-Snapshot13.vmsn[27.41K]

node3-Snapshot14.vmsn[27.42K]

node3-Snapshot15.vmsn[27.42K]

node3-Snapshot16.vmsn[27.41K]

node3-Snapshot17.vmsn[27.41K]

node3-Snapshot18.vmsn[27.42K]

node3-Snapshot19.vmsn[27.41K]

node3-Snapshot2.vmsn[27.39K]

node3-Snapshot20.vmsn[27.42K]

node3-Snapshot21.vmsn[27.42K]

node3-Snapshot3.vmsn[27.41K]

node3-Snapshot4.vmsn[27.41K]

node3-Snapshot5.vmsn[27.42K]

node3-Snapshot6.vmsn[27.42K]

node3-Snapshot7.vmsn[27.42K]

node3-Snapshot8.vmsn[27.42K]

node3-Snapshot9.vmsn[27.41K]

vmware.log[178.79K]

vmware-0.log[181.88K]

vmware-1.log[187.29K]

vmware-2.log[178.56K]

资料[9.07G]

centos7_镜像文件[4.34G]

CentOS-7-x86_64-DVD-1908.iso[4.34G]

CRT[42.53M]

手动安装版本CRT.zip[42.53M]

flink[791.11M]

相关jar包[466.77M]

antlr-runtime-3.5.2.jar[163.83K]

commons-cli-1.4.jar[52.56K]

flink-1.14.0-bin-scala_2.12.tgz[324.33M]

flink-connector-pulsar_2.12-1.14.0.jar[157.74K]

flink-shaded-hadoop-3-uber-3.1.1.7.2.9.0-173-9.0.jar[56.84M]

flink-sql-connector-hive-3.1.2_2.12-1.14.0.jar[46.49M]

hive-exec-3.1.2.jar[38.74M]

flink-1.14.0-bin-scala_2.12.tgz[324.33M]

hadoop-3.3.0[467.31M]

hadoop-3.3.0-Centos7-64-with-snappy.tar.gz[435.22M]

Hadoop3.3.0Linux编译安装.md[12.07K]

hadoop-3.3.0-src.tar.gz[32.07M]

hbase-2.1.0[253.50M]

hbase-2.1.0.tar.gz[253.50M]

hive3.1.2[857.36M]

hive3.1.2[266.82M]

mysql5.7.29[946.31K]

mysql-connector-java-5.1.32.jar[946.31K]

apache-hive-3.1.2-bin.tar.gz[265.90M]

hive3jdbc驱动[69.07M]

hive-jdbc-3.1.2-standalone.jar[69.07M]

mysql5.7.29[521.47M]

mysql-5.7.29-1.el7.x86_64.rpm-bundle.tar[520.55M]

mysql-connector-java-5.1.32.jar[946.31K]

jdk1.8[185.53M]

jdk-8u241-linux-x64.tar.gz[185.53M]

kafka[260.72M]

kafka一键化启动脚本[0.45K]

slave[0.05K]

start-kafka.sh[0.24K]

stop-kafka.sh[0.16K]

安装包[260.72M]

kafka-eagle工具[72.24M]

kafka-eagle-bin-1.4.6.tar.gz[72.24M]

kafka安装包[66.80M]

kafka_2.12-2.4.1.tgz[59.47M]

kafka-2.4.1-src.tgz[7.33M]

Kafka工具[113.64M]

kafkatool.dmg[54.21M]

kafkatool_64bit.exe[59.42M]

MySQL数据库工具[7.98M]

mysql-connector-java-5.1.38.jar[960.85K]

SQLyog-12.0.9-0.x64.exe[7.05M]

bzip2-0.9.1.jar[48.65K]

Phoenix[187.14M]

phoenix-hbase-2.1-5.1.2-bin.tar.gz[187.14M]

zookeeper[23.69M]

zookeeper客户端工具[1.80M]

build[1.64M]

classes[169.00K]

org[169.00K]

apache[169.00K]

zookeeper[169.00K]

inspector[162.31K]

encryption[1.18K]

BasicDataEncryptionManager.class[0.87K]

DataEncryptionManager.class[0.31K]

gui[131.92K]

nodeviewer[24.18K]

NodeViewerACL$1.class[5.00K]

NodeViewerACL.class[2.75K]

NodeViewerData$1.class[1.69K]

NodeViewerData$2.class[2.47K]

NodeViewerData.class[3.24K]

NodeViewerMetaData$1.class[4.11K]

NodeViewerMetaData.class[2.78K]

ZooInspectorNodeViewer.class[2.14K]

NodeViewersChangeListener.class[0.32K]

ZooInspectorAboutDialog$1.class[0.88K]

ZooInspectorAboutDialog.class[2.60K]

ZooInspectorConnectionPropertiesDialog$1.class[3.51K]

ZooInspectorConnectionPropertiesDialog$2.class[2.56K]

ZooInspectorConnectionPropertiesDialog$3.class[1.05K]

ZooInspectorConnectionPropertiesDialog.class[5.68K]

ZooInspectorIconResources.class[1.58K]

ZooInspectorNodeViewersDialog$1.class[1.48K]

ZooInspectorNodeViewersDialog$10.class[2.54K]

ZooInspectorNodeViewersDialog$11.class[1.02K]

ZooInspectorNodeViewersDialog$2.class[3.89K]

ZooInspectorNodeViewersDialog$3.class[1.84K]

ZooInspectorNodeViewersDialog$4.class[1.84K]

ZooInspectorNodeViewersDialog$5.class[1.86K]

ZooInspectorNodeViewersDialog$6.class[2.94K]

ZooInspectorNodeViewersDialog$7.class[3.71K]

ZooInspectorNodeViewersDialog$8.class[3.95K]

ZooInspectorNodeViewersDialog$9.class[3.28K]

ZooInspectorNodeViewersDialog.class[8.37K]

ZooInspectorNodeViewersPanel.class[4.77K]

ZooInspectorPanel$1.class[1.53K]

ZooInspectorPanel$2.class[0.89K]

ZooInspectorPanel$3.class[1.10K]

ZooInspectorPanel$4$1.class[2.04K]

ZooInspectorPanel$4.class[2.15K]

ZooInspectorPanel$5$1.class[2.16K]

ZooInspectorPanel$5.class[2.09K]

ZooInspectorPanel$6.class[1.63K]

ZooInspectorPanel$7.class[1.16K]

ZooInspectorPanel$8.class[2.79K]

ZooInspectorPanel$9.class[2.47K]

ZooInspectorPanel.class[8.46K]

ZooInspectorTreeViewer$1.class[1.46K]

ZooInspectorTreeViewer$2.class[1.41K]

ZooInspectorTreeViewer$3.class[1.53K]

ZooInspectorTreeViewer$4.class[2.45K]

ZooInspectorTreeViewer$ZooInspectorTreeCellRenderer.class[1.02K]

ZooInspectorTreeViewer$ZooInspectorTreeNode.class[4.61K]

ZooInspectorTreeViewer.class[7.14K]

logger[0.64K]

LoggerFactory.class[0.64K]

manager[25.54K]

NodeListener.class[0.33K]

Pair.class[2.33K]

ZooInspectorManager.class[1.43K]

ZooInspectorManagerImpl$NodeWatcher.class[3.07K]

ZooInspectorManagerImpl.class[16.80K]

ZooInspectorNodeManager.class[0.29K]

ZooInspectorNodeTreeManager.class[0.35K]

ZooInspectorReadOnlyManager.class[0.94K]

ZooInspector$1.class[0.90K]

ZooInspector.class[2.12K]

retry[6.69K]

ZooKeeperRetry.class[6.69K]

config[0.18K]

defaultNodeVeiwers.cfg[0.18K]

icons[4.38K]

edtsrclkup_co.gif[0.20K]

file_obj.gif[0.35K]

fldr_obj.gif[0.21K]

info_obj.gif[0.12K]

jspdecl.gif[0.19K]

launch_run.gif[0.37K]

launch_stop.gif[0.89K]

new_con.gif[0.34K]

refresh.gif[0.32K]

save_edit.gif[0.62K]

search_next.gif[0.32K]

search_prev.gif[0.32K]

trash.gif[0.13K]

lib[1.35M]

jtoaster-1.0.4.jar[14.62K]

log4j-1.2.15.jar[382.65K]

TableLayout-20050920.jar[10.05K]

zookeeper-3.3.0.jar[971.90K]

licences[28.33K]

ApacheSoftwareLicencev2.0.txt[11.09K]

epl-v10.html[12.34K]

TableLayoutLicense.txt[4.90K]

test

lib

zookeeper-dev-ZooInspector.jar[93.15K]

启动zookeeper.cmd[0.04K]

src[168.63K]

config[0.18K]

defaultNodeVeiwers.cfg[0.18K]

icons[4.38K]

edtsrclkup_co.gif[0.20K]

file_obj.gif[0.35K]

fldr_obj.gif[0.21K]

info_obj.gif[0.12K]

jspdecl.gif[0.19K]

launch_run.gif[0.37K]

launch_stop.gif[0.89K]

new_con.gif[0.34K]

refresh.gif[0.32K]

save_edit.gif[0.62K]

search_next.gif[0.32K]

search_prev.gif[0.32K]

trash.gif[0.13K]

lib[14.62K]

jtoaster-1.0.4.jar[14.62K]

licences[28.33K]

ApacheSoftwareLicencev2.0.txt[11.09K]

epl-v10.html[12.34K]

TableLayoutLicense.txt[4.90K]

src[113.68K]

java[113.68K]

org[113.68K]

apache[113.68K]

zookeeper[113.68K]

inspector[105.60K]

encryption[2.53K]

BasicDataEncryptionManager.java[1.33K]

DataEncryptionManager.java[1.20K]

gui[72.11K]

nodeviewer[17.57K]

NodeViewerACL.java[5.21K]

NodeViewerData.java[4.27K]

NodeViewerMetaData.java[4.53K]

ZooInspectorNodeViewer.java[3.56K]

about.html[0.99K]

NodeViewersChangeListener.java[0.36K]

ZooInspectorAboutDialog.java[2.54K]

ZooInspectorConnectionPropertiesDialog.java[6.64K]

ZooInspectorIconResources.java[2.74K]

ZooInspectorNodeViewersDialog.java[16.72K]

ZooInspectorNodeViewersPanel.java[3.77K]

ZooInspectorPanel.java[10.96K]

ZooInspectorTreeViewer.java[9.84K]

logger[1.07K]

LoggerFactory.java[1.07K]

manager[27.89K]

NodeListener.java[0.93K]

Pair.java[2.36K]

ZooInspectorManager.java[2.81K]

ZooInspectorManagerImpl.java[17.49K]

ZooInspectorNodeManager.java[0.96K]

ZooInspectorNodeTreeManager.java[1.11K]

ZooInspectorReadOnlyManager.java[2.22K]

ZooInspector.java[2.01K]

retry[8.08K]

ZooKeeperRetry.java[8.08K]

build.xml[5.90K]

ivy.xml[1.52K]

zookeeper-3.4.6.tar.gz[16.88M]

综合案例[83.64M]

flume[64.79M]

apache-flume-1.9.0-bin.tar.gz[64.79M]

生产数据工具[18.85M]

MoMo_Data.xlsx[40.13K]

MoMo_DataGen.jar[18.81M]

ccsetup569-断网激活_C2YW-XZT7-A4SE-UD89-YZPC.exe[26.76M]

Spark.zip[1.62G]

2021_新版本软件安装_v5_20211002_192.168.88.2_安装Spark-NoSQL-Flink.docx[15.14M]

centos_20211005.zip.001[7.96G]

centos_20211005.zip.002[7.96G]

centos_20211005.zip.003[7.96G]

centos_20211005.zip.004[7.96G]

centos_20211005.zip.005[5.66G]

说明1：1-7快照截图.jpg[26.30K]

说明2.txt[0.19K]

资料[2.43G]

hadoop-3.3.0[3.29M]

bin[3.29M]

hadoop.dll[85.00K]

hadoop.exp[19.30K]

hadoop.lib[32.46K]

hadoop.pdb[684.00K]

libwinutils.lib[1.25M]

winutils.exe[110.00K]

winutils.pdb[1.13M]

测试数据[123.03M]

sql[1.89M]

hello_world.txt[0.04K]

people.csv[0.18K]

people.json[0.07K]

people.txt[0.03K]

stu_score.avi[1.20K]

stu_score.txt[1.20K]

u.data[1.89M]

user.avsc[0.18K]

users.avro[0.33K]

users.orc[0.53K]

users.parquet[0.60K]

tiny_files[0.19K]

1.txt[0.04K]

2.txt[0.04K]

3.txt[0.04K]

4.txt[0.04K]

5.txt[0.04K]

accumulator_broadcast_data.txt[0.21K]

apache.log[1.41K]

mini.json[118.62M]

minimini.json[1.17M]

order.text[2.84K]

SogouQ.txt[1.34M]

stu_info.txt[0.32K]

stu_score.txt[1.20K]

words.txt[0.04K]

Anaconda3-2021.05-Linux-x86_64.sh[544.41M]

Anaconda3-2021.05-Windows-x86_64.exe[477.20M]

apache-hive-3.1.2-bin.tar.gz[265.90M]

DAG和Action.drawio[2.30K]

hadoop-3.3.1.tar.gz[577.15M]

jdk-8u211-linux-x64.tar.gz[185.96M]

mysql-connector-java-5.1.41-bin.jar[969.54K]

mysql-connector-java-8.0.13.jar[2.03M]

pyarrow-4.0.1-cp38-cp38-manylinux2014_x86_64.whl[20.87M]

SparkOnYARNClient模式.drawio[2.12K]

SparkOnYARNCluster模式.drawio[1.98K]

spark-3.2.0-bin-hadoop3.2.tgz[287.02M]

Spark部署文档.md[28.93K]

Spark层次关系概念图.png[118.54K]

Spark核心概念.png[724.93K]

Spark核心概念.xmind[746.76K]

WordCount代码执行的图示.drawio[2.27K]