 Stream ingestion and pub/sub systems - CS 591 K1: Data Stream Processing and Analytics Spring 2020message - many-to-many communication - message content / structure matters for delivery 8 MB architecture advantages • Multiple producers/consumers as concurrent clients • Effective failure handling If consumers are slow, throughput might degrade. • DBs support secondary indexes for efficient search while MBs only offer topic-based subscription. • DB query results depend on a snapshot and clients0 码力 | 33 页 | 700.14 KB | 1 年前3 Stream ingestion and pub/sub systems - CS 591 K1: Data Stream Processing and Analytics Spring 2020message - many-to-many communication - message content / structure matters for delivery 8 MB architecture advantages • Multiple producers/consumers as concurrent clients • Effective failure handling If consumers are slow, throughput might degrade. • DBs support secondary indexes for efficient search while MBs only offer topic-based subscription. • DB query results depend on a snapshot and clients0 码力 | 33 页 | 700.14 KB | 1 年前3
 Course introduction - CS 591 K1: Data Stream Processing and Analytics Spring 2020about? The design and architecture of modern distributed streaming 4 Fundamental for representing, summarizing, and analyzing data streams Systems Algorithms Architecture and design Scheduling0 码力 | 34 页 | 2.53 MB | 1 年前3 Course introduction - CS 591 K1: Data Stream Processing and Analytics Spring 2020about? The design and architecture of modern distributed streaming 4 Fundamental for representing, summarizing, and analyzing data streams Systems Algorithms Architecture and design Scheduling0 码力 | 34 页 | 2.53 MB | 1 年前3
 Introduction to Apache Flink and Apache Kafka - CS 591 K1: Data Stream Processing and Analytics Spring 2020(live,1) (and,1) (let,1) (live,2) 4 Vasiliki Kalavri | Boston University 2020 Distributed architecture client Flink program JobManager web dashboard TaskManager TaskManager TaskManager 50 码力 | 26 页 | 3.33 MB | 1 年前3 Introduction to Apache Flink and Apache Kafka - CS 591 K1: Data Stream Processing and Analytics Spring 2020(live,1) (and,1) (let,1) (live,2) 4 Vasiliki Kalavri | Boston University 2020 Distributed architecture client Flink program JobManager web dashboard TaskManager TaskManager TaskManager 50 码力 | 26 页 | 3.33 MB | 1 年前3
 Filtering and sampling streams - CS 591 K1: Data Stream Processing and Analytics Spring 2020can store a fixed proportion of the stream, e.g. 1/10th 7 search engine Filtering and sampling streams - CS 591 K1: Data Stream Processing and Analytics Spring 2020can store a fixed proportion of the stream, e.g. 1/10th 7 search engine- query stream Example use-case: Web search user behavior study Q: How many queries did users repeat last 0 码力 | 74 页 | 1.06 MB | 1 年前3
 Graph streaming algorithms - CS 591 K1: Data Stream Processing and Analytics Spring 2020way to reach Zurich from London through Berlin? These are the top-10 relevant results for the search term “graph” ??? Vasiliki Kalavri | Boston University 2020 Basics 1 5 4 3 2 “node” or “vertex”0 码力 | 72 页 | 7.77 MB | 1 年前3 Graph streaming algorithms - CS 591 K1: Data Stream Processing and Analytics Spring 2020way to reach Zurich from London through Berlin? These are the top-10 relevant results for the search term “graph” ??? Vasiliki Kalavri | Boston University 2020 Basics 1 5 4 3 2 “node” or “vertex”0 码力 | 72 页 | 7.77 MB | 1 年前3
 Stream processing fundamentals - CS 591 K1: Data Stream Processing and Analytics Spring 2020• The number of distinct users who have visited a website? • The top-10 queries inserted in a search engine? • The connected components of accounts in a stream of financial transactions? What synopsis0 码力 | 45 页 | 1.22 MB | 1 年前3 Stream processing fundamentals - CS 591 K1: Data Stream Processing and Analytics Spring 2020• The number of distinct users who have visited a website? • The top-10 queries inserted in a search engine? • The connected components of accounts in a stream of financial transactions? What synopsis0 码力 | 45 页 | 1.22 MB | 1 年前3
 PyFlink 1.15 Documentationpage in the official Flink documen- tation. For example, you can open the Kafka connector page and search keyword “SQL Client JAR” which is a fat JAR of Kafka connector. • It should be noted that you should0 码力 | 36 页 | 266.77 KB | 1 年前3 PyFlink 1.15 Documentationpage in the official Flink documen- tation. For example, you can open the Kafka connector page and search keyword “SQL Client JAR” which is a fat JAR of Kafka connector. • It should be noted that you should0 码力 | 36 页 | 266.77 KB | 1 年前3
 PyFlink 1.16 Documentationpage in the official Flink documen- tation. For example, you can open the Kafka connector page and search keyword “SQL Client JAR” which is a fat JAR of Kafka connector. • It should be noted that you should0 码力 | 36 页 | 266.80 KB | 1 年前3 PyFlink 1.16 Documentationpage in the official Flink documen- tation. For example, you can open the Kafka connector page and search keyword “SQL Client JAR” which is a fat JAR of Kafka connector. • It should be noted that you should0 码力 | 36 页 | 266.80 KB | 1 年前3
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