computation maintains state: • rolling aggregations • window contents • input offsets • machine learning models State in dataflow computations 2 Vasiliki Kalavri | Boston University 2020 • No explicit in Apache Flink - Tzu-Li (Gordon) Tai: https:// www.youtube.com/watch?v=euFMWFDThiE • Webinar: Deep Dive on Apache Flink State - Seth Wiesman: https:// www.youtube.com/watch?v=9GF8Hwqzwnk Further

computation maintains state: • rolling aggregations • window contents • input offsets • machine learning models State in dataflow computations 3 Vasiliki Kalavri | Boston University 2020 Logic State computation maintains state: • rolling aggregations • window contents • input offsets • machine learning models State in dataflow computations 3 Vasiliki Kalavri | Boston University 2020 Logic State computation maintains state: • rolling aggregations • window contents • input offsets • machine learning models State in dataflow computations 3 Vasiliki Kalavri | Boston University 2020 4 Distributed

Batch API Historic data Kafka, RabbitMQ, ... HDFS, JDBC, ... Event logs ETL, Graphs,
 Machine Learning
 Relational, … Low latency,
 windowing, aggregations, ... 2 Vasiliki Kalavri | Boston University

workloads, such as real-time data processing pipelines, large-scale exploratory data analysis, Machine Learning (ML) pipelines and ETL processes. If you’re already familiar with Python and libraries such as Pandas

workloads, such as real-time data processing pipelines, large-scale exploratory data analysis, Machine Learning (ML) pipelines and ETL processes. If you’re already familiar with Python and libraries such as Pandas

setMaxParallelism(1024) 33 Setting the max parallelism ??? Vasiliki Kalavri | Boston University 2020 • A Deep Dive into Rescalable State in Apache Flink: https:// flink.apache.org/features/2017/07/04/flink-rescalable-state