SYSTEM AND METHOD FOR DETERMINING AN AMOUNT OF VIRTUAL MACHINES FOR USE WITH EXTRACT, TRANSFORM, LOAD (ETL) PROCESSES

    公开(公告)号:US20200334089A1

    公开(公告)日:2020-10-22

    申请号:US16852509

    申请日:2020-04-19

    Abstract: In accordance with an embodiment, described herein are systems and methods for determining or allocating an amount, quantity, or number of compute instances or virtual machines for use with extract, transform, load (ETL) processes. In an example embodiment, a particular (e.g., optimal) number of virtual machines (VM's) can be determined by predicting ETL completion times for customers, using historical data. ETL processes can be simulated with an initial/particular number of virtual machines. If the predicted duration is greater than the desired duration, the number of virtual machines can be incremented, and the simulation repeated. Actual completion times from ETL processes can be fed back, to update a determined number of compute instances or virtual machines. In accordance with an embodiment, the system can be used, for example, to generate alerts associated with customer service level agreements (SLA's).

    SYSTEM AND METHOD FOR LOAD PLAN INTELLIGENT RUN IN A MULTIDIMENSIONAL DATABASE

    公开(公告)号:US20170161344A1

    公开(公告)日:2017-06-08

    申请号:US15182320

    申请日:2016-06-14

    CPC classification number: G06F16/254 G06F16/283

    Abstract: In accordance with an embodiment, an intelligent load plan that can automatically ensure that a system is in a runnable state and no other conflicting activity can affect the results of the data loads, such as ETLs. Such an intelligent load plan can be used in on data warehousing solutions as well as on a cloud data warehouse solution. The intelligent load plan can, in some embodiments, automatically detect situations based on which it knows it is not supposed to run the load plan.

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