Azure Data Lake Jobs: Making Big Data Easy

Play Azure Data Lake Jobs: Making Big Data Easy


This episode of Data Exposed welcomes back Saveen Reddy, a Principal PM on the Azure Data Lake team. Scott and Saveen follow up the Azure Data Lake Explained episode with a show about, as Saveen puts it, "how we're making big data easy".  Saveen and his group focus on how to make developers productive with big data, specifically around the tooling and language aspects. On today's show, Saveen introduces us to U-SQL optimization with Data Lake Tools for Visual Studio which is installed with the Azure SDK. U-SQL jobs provide the ability to do analytics at scale and Saveen shows how easy it is to debug and optimize for performance at scale. Saveen shows us the U-SQL job graph/execution plan that is generated from a Data Lake U-SQL script and the analysis tools that help developers understand key performance hotspots and opportunities for optimization.

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The Discussion

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    Ilya Geller

    Meanwhile Oracle structures data:
    1. Oracle obtains statistics on queries and data from the data itself, internally'.
    3. Oracle gets 100% patterns from data.
    4. Oracle uses synonyms searching.
    5. Oracle indexes data by common dictionary.
    6. Oracle killed SQL: SQL, Structured Query Language either does not use statistics at all or uses manually assigned one.

    Microsoft uses SQL databases only for its cloud platforms, which
    1. Manually assign statistics.
    2. Get 1-5% of patterns from data.
    3. Cannot use synonyms.
    4. Do not index data.
    5. Do not use dictionary.
    5. Use the obsolete and dead SQL.

    Microsoft is to lose to Oracle.
    You can say Oracle puts Internet into database and owns all database industry.

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