PyFlink 1.15 Documentationfor use: curl -L https://raw.githubusercontent.com/apache/flink/master/flink-python/pyflink/ ˓→examples/table/word_count.py -o word_count.py python3 word_count.py # You will see outputs as following: following: curl -L https://raw.githubusercontent.com/apache/flink/master/flink-python/pyflink/ ˓→examples/table/word_count.py -o word_count.py python3 word_count.py If there any any problems, you could -Dkubernetes.container.image=\ --pyModule word_count \ --pyFiles /opt/flink/examples/python/table/word_count.py Execute PyFlink jobs in session mode with Native Kubernetes You could 0 码力 | 36 页 | 266.77 KB | 1 年前3
PyFlink 1.16 Documentationfor use: curl -L https://raw.githubusercontent.com/apache/flink/master/flink-python/pyflink/ ˓→examples/table/word_count.py -o word_count.py python3 word_count.py # You will see outputs as following: following: curl -L https://raw.githubusercontent.com/apache/flink/master/flink-python/pyflink/ ˓→examples/table/word_count.py -o word_count.py python3 word_count.py If there any any problems, you could -Dkubernetes.container.image=\ --pyModule word_count \ --pyFiles /opt/flink/examples/python/table/word_count.py Execute PyFlink jobs in session mode with Native Kubernetes You could 0 码力 | 36 页 | 266.80 KB | 1 年前3
Course introduction - CS 591 K1: Data Stream Processing and Analytics Spring 2020Deliverables • One (1) written report of maximum 5 pages (10%). • Code (including pre-processing, deployment, and testing): (40%) • code deliverables must be accompanied by documentation 8 Vasiliki Kalavri less than 15% of all data. 18 Vasiliki Kalavri | Boston University 2020 Can you give me some examples of streaming data sources? 19 Vasiliki Kalavri | Boston University 2020 20 Location-based services applications • Complex filtering and alarm activation • Aggregation of multiple sensors and joins • Examples • Real-time statistics, e.g. weather maps • Monitor conditions to adjust resources, e.g. power0 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 2020application with no arguments: ./bin/flink run ./examples/batch/WordCount.jar Run an application with input and output arguments: ./bin/flink run ./examples/batch/WordCount.jar \ --input class entry point and arguments: ./bin/flink run -c org.apache.flink.examples.java.wordcount.WordCount \ ./examples/batch/WordCount.jar \ --input file:///home/user/hamlet0 码力 | 26 页 | 3.33 MB | 1 年前3
Streaming in Apache FlinkArray • composite types: Tuples, POJOs, and Scala case classes • Kryo for unknown types Type Examples Tuples Tuple1 through Tuple25 types. POJOs A POJO (plain old Java object) is any Java class0 码力 | 45 页 | 3.00 MB | 1 年前3
Cardinality and frequency estimation - CS 591 K1: Data Stream Processing and Analytics Spring 2020comparing them with yesterday’s frequencies provides an indication of what is “trending” Motivating examples ??? Vasiliki Kalavri | Boston University 2020 19 • Expand the classical BF with an array of m0 码力 | 69 页 | 630.01 KB | 1 年前3
Scalable Stream Processing - Spark Streaming and Flinkfunction is executed in the driver process. 31 / 79 Output Operations (2/4) ▶ What’s wrong with this code? ▶ This requires the connection object to be serialized and sent from the driver to the worker. send(record) // executed at the worker } } 32 / 79 Output Operations (2/4) ▶ What’s wrong with this code? ▶ This requires the connection object to be serialized and sent from the driver to the worker. send(record) // executed at the worker } } 32 / 79 Output Operations (3/4) ▶ What’s wrong with this code? ▶ Creating a connection object has time and resource overheads. ▶ Creating and destroying a connection0 码力 | 113 页 | 1.22 MB | 1 年前3
Apache Flink的过去、现在和未来Continuous Processing & Streaming Analytics Event-driven Applications ✔ ✔ ✔ 扫码加入社群 与志同道合的码友一起 Code Up 阿里云开发者社区 Apache Flink China 2群 粘贴二维码 谢谢!0 码力 | 33 页 | 3.36 MB | 1 年前3
High-availability, recovery semantics, and guarantees - CS 591 K1: Data Stream Processing and Analytics Spring 2020• Retries simply replay the output that has been checkpointed, i.e. the user’s non- deterministic code is not re-executed Bloom filters for performance • Maintaining a catalog of all IDs ever seen0 码力 | 49 页 | 2.08 MB | 1 年前3
监控Apache Flink应用程序(入门)time window) for functional reasons. 4. Each computation in your Flink topology (framework or user code), as well as each network shuffle, takes time and adds to latency. 5. If the application emits0 码力 | 23 页 | 148.62 KB | 1 年前3
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