40 lines
1.6 KiB
Markdown
40 lines
1.6 KiB
Markdown
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# Learning Resources
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This documents contains a list of papers articles etc. that are useful for understanding the design of IFQL.
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## Stream Processing
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* Set of articles by Tyler Akidau on building stream processing engines with correctness guarantees.
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https://www.oreilly.com/ideas/the-world-beyond-batch-streaming-101
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https://www.oreilly.com/ideas/the-world-beyond-batch-streaming-102
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* Published paper by Tyler AKidau on building stream processing engines with correctness guarantees.
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http://www.vldb.org/pvldb/vol8/p1792-Akidau.pdf
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* Paper from UC Berkley introducing Spark and RDDs
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https://www.usenix.org/system/files/conference/nsdi12/nsdi12-final138.pdf
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* A summary of the different data APIs in Spark
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https://databricks.com/blog/2016/07/14/a-tale-of-three-apache-spark-apis-rdds-dataframes-and-datasets.html
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## Map Reduce
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* Google research paper on Dremel
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https://research.google.com/pubs/pub36632.html
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## DataFrames
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* Good overview on various sparse matrix implementations. https://en.wikipedia.org/wiki/Sparse_matrix
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## Query Optimization
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* Volcano Optimizer Generator
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https://pdfs.semanticscholar.org/a817/a3e74d1663d9eb35b4baf3161ab16f57df85.pdf
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* The Cascades Framework for Query Optimization
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http://db.informatik.uni-mannheim.de/downloads/hauptstudium/seminare/papers/Cascades_01.PDF
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* Chapter 7: Query Optimization
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From Readings in Database Systems, 5th Edition (2015)
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http://www.redbook.io/pdf/ch7-queryoptimization.pdf
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This chaper references various other valuable readings.
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* Cost-based Optimization in Parallel Data Frameworks
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https://www.cse.iitb.ac.in/~pararth09/btp/report.pdf
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