A[j]) and updates arrive in increasing order of j, i.e. we observe the entries of A by increasing index. This can model time-series data streams: • a sequence of measurements from a temperature sensor various ways: • as the concatenation of serializations of the relations. • as a list of tuple-index pairs, where indicates that t ∈ rj • as a serialization of r1 followed by a series of delta EOR (1, 2, 20K), (2, 5, 32K), (2, 3, 28K) EOR (2, 5, 32K), (2, 3, 28K), (1, 2, 28K) EOR • tuple-index pairs <(1, 2, 20K), 1>, <(2, 5, 32K), 2>, <(1, 2, 20K), 2>, <(2, 5, 32K), 1>, <(2, 3, 28K), 3>, <(2

locate and read the matching keys only • Avoids reading irrelevant data • Requires a materialized index for all keys, i.e. a key-to-read-offset mapping, which can potentially grow very large • Large parallel instance • Some kind of hashing is typically used • Maintaining routing tables or an index for all key mappings is usually impractical • Skewed load is challenging to handle with hashing

response vehicles • Read more: https://edition.cnn.com/2019/01/15/tech/alibaba-city- brain-hangzhou/index.html 27 Vasiliki Kalavri | Boston University 2020 Why is stream processing challenging? 28

getter and setter Tuple2 person = new Tuple2<>("Fred", 35); // zero based index! String name = person.f0; Integer age = person.f1; public class Person { public String

of a near-optimal cardinality estimation algorithm. 2007. https://hal.archives-ouvertes.fr/file/index/docid/406166/ filename/FlFuGaMe07.pdf • Cormode, Graham, and Shan Muthukrishnan. An improved data

pandoc 3. Build the docs python3 setup.py build_sphinx 4. Open the pyflink-docs/build/sphinx/html/index.html in the Browser 1.1 Getting Started This page summarizes the basic steps required to setup and

pandoc 3. Build the docs python3 setup.py build_sphinx 4. Open the pyflink-docs/build/sphinx/html/index.html in the Browser 1.1 Getting Started This page summarizes the basic steps required to setup and