Udemy線上課程 Apache Flink 1.17.x DataStream API Streaming 即時計算完全教程 講師:Alexander Wong 影音教學 中文發音 繁體中文(2DVD)
Udemy線上課程 Apache Flink 1.17.x DataStream API Streaming 即時計算完全教程 講師:Alexander Wong 影音教學 中文發音 繁體中文(2DVD)
內容說明:
非常感謝您能夠購買我的課程，這是一門關於Apache Flink 1.17.x的完全教學影片，在該影片中我會非常詳細由淺入深的介紹並且練習每一個Apache Flink框架的使用細節.
Apache Flink 是一個框架和分散式處理引擎，用於對無界和有界資料流進行狀態計算。
Flink 被設計為在所有常見的叢集環境中運行，以記憶體速度和任何規模執行計算。
【課程特色】代碼驅動大量的案例由淺入深課程內容緊湊涵蓋絕大多數Apache Flink框架的內容豐富的綜合案例
[課程大綱]Apache Flink 1.17.2 快速開始詳細講解Apache Flink 1.17.2 Job Deployment Mode詳細講解Apache Flink 1.17.2 運行時架構詳細講解Apache Flink 1.17.2 DataStream API及即時應用開發詳細講解Apache Flink 1.17.2 Window API及即時應用開發深入解讀Apache Flink 1.17.2 Watermark-處理遲到和亂序數據詳細講解Apache Flink 1.17.2 Stateful operators and Application詳細講解Apache Flink 1.17.2 Checkpoints & SavePoints & Exactly Once Semantic
希望你能夠喜歡這門課程，經過這門課程的學習，您將成為Apache Flink的專家，並且能夠基於Apache Flink構建複雜即時事件處理應用程式
課程內容:
01 - Apache Flink 1.17.2 課程介紹
001 Prerequisites.mp4
002 Course Objective.mp4
003 課程介紹.mp4
02 - Apache Flink 1.17.2 快速開始
001 第一部分(Flink QuickStart)內容概要.mp4
002 Apache Flink的基本介紹.mp4
003 Apache Flink的特色介紹.mp4
004 Apache Flink的使用場景.mp4
005 Apache Flink的架構預覽.mp4
006 Flink獨立叢集安裝.mp4
007 Flink叢集的啟動及停止.mp4
008 Flink DataSet API處理離線檔.mp4
009 Flink DataStream API處理離線文件.mp4
010 Flink Runtime Execution Mode.mp4
011 Flink DataStream處理流數據.mp4
012 Flink DataStream API and Java Lambda表達式.mp4
013 使用Job Manager的WebUI提交Flink Job.mp4
014 使用Flink命令行提交Flink Job.mp4
03 - 詳細講解Apache Flink 1.17.2 Job Deployment Mode
001 第二部分(Flink Job Deployment Mode)內容摘要.mp4
002 Session Mode,Per-Job Mode和Application Mode概述.mp4
003 Flink job Session deploy Mode的優缺點.mp4
004 Flink job Per-Job Deploy Mode的優缺點.mp4
005 Flink job Application Deploy Mode的優缺點.mp4
006 Session Mode Under Standalone Cluster.mp4
007 Application Mode Under Standalone Cluster.mp4
008 Hadoop叢集的安裝與準備.mp4
009 Session Mode Under Yarn Resource Provider.mp4
010 Per-Job Mode Under Yarn Resource Provider.mp4
011 Application Mode Under Yarn Resource Provider.mp4
012 進一步優化Application Mode的作業提交.mp4
013 Flink Job History Server配置以及啟動.mp4
04 - 詳細講解Apache Flink 1.17.2 運行時架構
001 第三部分(Apache Flink Runtime Architecture)內容概要.mp4
002 Apache Flink運行時架構與內部組件詳解.mp4
003 Apache Flink Slots,Tasks,SubTasks概念的介紹.mp4
004 Apache Flink Local Environment For Develop.mp4
005 Apache Flink job operator parallelism.mp4
006 Apache Flink operator並行度優先權詳解.mp4
007 Apache Flink operator chaining介紹.mp4
008 什麼情況下會發生Operator chaining.mp4
009 Apache Flink Operator Chaining API and Programming.mp4
010 Apache Flink Shard Slots Group.mp4
011 Apache Flink Job提交執行的流程-Standalone叢集下的Session Deploy Mode.mp4
012 Apache Flink Job提交執行的流程-Yarn叢集下的Per-Job Deploy Mode.mp4
013 Apache Flink Job提交執行的流程-Yarn叢集下的Session Deploy Mode.mp4
014 深入學習 Apache Flink's data flow graphs.mp4
05 - 詳細講解Apache Flink 1.17.2 DataStream API及即時應用開發
001 第四部分(Apache Flink 1.17.2 DataStream API)內容概要.mp4
002 Source Collector-Java Collections.mp4
003 Source Collector-DataGen.mp4
004 Source Collector-TCP Socket.mp4
005 Source Collector-FileSystem以StreamFormat讀取處理本機文件.mp4
006 Source Collector-FileSystem以BulkFormat讀取處理本機文件.mp4
007 Source Collector-Hdfs File source connector.mp4
008 Source Collector-Mongodb source connector.mp4
009 Source Collector-Kafka source connector consume text data.mp4
010 Source Collector-Kafka source connector consume JSON data.mp4
011 Source Collector-Kafka source connector consume K,V data.mp4
012 Source Collector-Custom RichSourceFunction.mp4
013 Source Collector-Custom RichParallelSourceFunction.mp4
014 Flink Data Types and TypeInformation.mp4
015 Stream Data Transformations.mp4
016 MAP,FILTER,FLATMAP Transformation.mp4
017 KeyBy and KeyedStream.mp4
018 KeyedStream Rolling Aggregation.mp4
019 KeyedStream ReduceFunction.mp4
020 Multistream Merge Operator - UNION.mp4
021 Multistream Merge Operator-CONNECT(fire alarm application-I).mp4
022 Multistream Merge Operator-CONNECT(fire alarm application-II).mp4
023 Multistream Connect Operator-DataStreams Inner Join.mp4
024 Split Data Stream-Side Output Stream.mp4
025 RichFunction and Handling Application Parameters.mp4
026 Data Exchange Strategies and Algorithms.mp4
027 Forward Partitioner Algorithm.mp4
028 Shuffle Partitioner Algorithm.mp4
029 Rebalance Partitioner Algorithm.mp4
030 Broadcast Partitioner Algorithm.mp4
031 Global Partitioner Algorithm.mp4
032 KeyGroupStream Partitioner Algorithm.mp4
033 Rescale Partitioner Algorithm.mp4
034 Custom Partitioner Algorithm.mp4
035 How to apply Accumulators & Counters.mp4
036 Sink Collector-Socket Sink Connector.mp4
037 Sink Collector-LocalFileSystem Sink Connector(TXT).mp4
038 Sink Collector-LocalFileSystem Sink Connector(AVRO).mp4
039 Sink Collector-LocalFileSystem Sink Connector(Parquet).mp4
040 Sink Collector-Hdfs FileSystem Sink Connector(Avro).mp4
041 Sink Collector-JDBC Sink Connector.mp4
042 Sink Collector-Kafka Sink Connector(Value Only).mp4
043 Sink Collector-Kafka Sink Connector(Key and Value).mp4
044 Sink Collector-Kafka Sink Connector(JSON).mp4
045 Sink Collector-Mongodb Sink Connector.mp4
046 自定義sink collector(old API).mp4
047 自定義sink collector(new API).mp4
06 - 詳細講解Apache Flink 1.17.2 Window API及即時應用開發
001 第五部分(Apache Flink 1.17.2 Window API)內容概要.mp4
002 Keyed Window和No-Keyed Window之間的差異.mp4
003 深入解析No-Keyed Window實作原理.mp4
004 深入解析Flink Keyed Window的定義以及源碼分析.mp4
005 Flink 支援的幾種Window類別.mp4
006 Flink Window的生命週期.mp4
007 如何建立Tumbling Process TimeWindow並建置Streaming Application-I.mp4
008 如何建立Tumbling Process TimeWindow並建置Streaming Application-II.mp4
009 深入Flink原始碼進一步分析Window的運算與輸出邏輯.mp4
010 Sliding Process TimeWindow詳解.mp4
011 Session Process TimeWindow詳解.mp4
012 Global TimeWindow詳解.mp4
013 Count Window詳解.mp4
014 WindowedStream Rolling Aggregation Function詳解.mp4
015 WindowedStream reduce operator and ReduceFunction詳解.mp4
016 WindowedStream aggregate operator and AggregateFunction詳解.mp4
017 WindowedStream process operator and ProcessWindowFunction詳解.mp4
018 WindowedStream Side Output詳解.mp4
019 WindowedStream window function結合incrementally function(最佳實務).mp4
020 WindowedStream apply operator and WindowFunction(Legacy)詳解.mp4
021 WindowedStream Trigger& Trigger API & TriggerResult 詳細講解.mp4
022 WindowedStream 深入Trigger源碼剖析工作原理-I.mp4
023 WindowedStream 深入Trigger源碼剖析工作原理-II.mp4
024 WindowedStream 深入Trigger源碼剖析工作原理-III.mp4
025 WindowedStream如何自定義以及應用Window Trigger-I.mp4
026 WindowedStream如何自定義以及應用Window Trigger-II.mp4
027 WindowedStream Evictor 詳解以及自定義Evictor.mp4
028 Timer and TimerService介紹.mp4
029 深入Timer和TimerService的工作內幕.mp4
07 - 深入解讀Apache Flink 1.17.2 Watermark-處理遲到和亂序數據
001 第六部分(Apache Flink 1.17.2 Watermark)內容概要.mp4
002 Time Semantics Introduce.mp4
003 Process Time and Event Time Introduce.mp4
004 什麼是Flink Watermark(Watermark需要解決哪些問題).mp4
005 Watermark的生成演算法演進講解.mp4
006 透過程式再現亂序數據和遲到數據.mp4
007 在視窗計算中如何處理亂序數據和遲到數據.mp4
008 Flink Watermark Strategy詳細解說.mp4
009 深入分析Flink Watermark Strategy源碼.mp4
010 自定義Flink Watermark Generator.mp4
011 多並行度下的watermark傳遞詳細講解.mp4
012 透過閱讀原始碼進一步深入分析Flink中Watermark傳遞機制與原理.mp4
013 如何處理空閒source的watermark傳遞.mp4
014 WindowedStream Allowed Lateness詳細解說.mp4
015 WindowedStream透過測輸出流獲取遲到資料避免遺失.mp4
016 JoinedStreams window join詳細講解.mp4
017 KeyedStream interval join詳細講解.mp4
08 - 詳細講解Apache Flink 1.17.2 Stateful operators and Application
001 第七部分(Apache Flink 1.17.2 Stateful operators and Application)內容概要.mp4
002 Stateful Operator and Stateful Application.mp4
003 Flink中關于State的分類.mp4
004 Flink Keyed State之ValueState使用詳細講解.mp4
005 Flink Keyed State之ReducingState使用詳細講解.mp4
006 Flink Keyed State之AggregatingState使用詳細講解.mp4
007 Flink Keyed State之ListState使用詳細講解(TopN Example).mp4
008 Flink Keyed State之MapState使用詳細講解.mp4
009 Flink State Time to Live(TTL) 配置及應用.mp4
010 Flink Operator State詳細講解.mp4
011 Flink Stateful Source Collector(CheckpointedFunction).mp4
012 Flink Stateful Source Operator State Application開發及測試.mp4
013 Flink Broadcast State詳細講解.mp4
014 Flink State Backend之HashMapStateBackend詳細講解.mp4
015 Flink State Backend之EmbeddedRocksDBStateBackend詳細講解.mp4
016 Flink State Questions And Answers.mp4
09 - 詳細講解Apache Flink 1.17.2 Checkpoints & SavePoints & Exactly Once Semantic
001 第八部分(Apache Flink 1.17.2 Checkpoints & SavePoints & Exactly Once Semantic)內容概要.mp4
002 Flink Consistent Checkpoints.mp4
003 Flink Consistent Checkpoints算法-Instant Checkpoints.mp4
004 Flink Consistent Checkpoints算法-Periodically Checkpoints.mp4
005 Flink Consistent Checkpoints算法-Chandy-Lamport.mp4
006 Flink Checkpoints and JobManager Checkpoints Coordinator.mp4
007 Flink Checkpoints的基本配置與啟用.mp4
008 Flink Checkpoints Barrier Alignment and Exactly Once配置.mp4
009 Checkpoints Barrier Alignment and At Least Once配置.mp4
010 Flink Checkpoints Barrier Unalignment and Exactly Once配置.mp4
011 Flink savepoints introduction and restoring application state from savepoints.mp4
012 How to apply savepoints when you resume Flink Application.mp4
013 Trigger Savepoints when stop the Flink Job.mp4
014 Flink Checkpoints vs Savepoints.mp4
015 Flink Application End to End Exactly Once Semantics.mp4
016 Flink EOS Application - Idempotent writes.mp4
017 Flink EOS Application - Generic write-ahead-log (WAL) sink.mp4
018 Flink EOS Application - TwoPhaseCommit Sink.mp4
019 Flink work with Apache Kafka implement the End to End Exactly Once Semantics-I.mp4
020 Flink work with Apache Kafka implement the End to End Exactly Once Semantics-II.mp4
021 Flink work with Apache Kafka implement the End to End Exactly Once Semantics-III.mp4
022 Flink New Data Source Collector Specification.mp4
023 Flink New Data Source Collector自定義-I.mp4
024 Flink New Data Source Collector自定義-II.mp4
025 Flink New Data Source Collector自定義-III.mp4
10 - Materials & Source Code Download
001 apache-flink-1.17.pptx
001 Feel Free To Download.html
001 flink-1.17.2-learning.zip
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