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alexira [117]
3 years ago
14

You are a data engineer implementing a lambda architecture on Microsoft Azure. You use an open-source big data solution to colle

ct, process, and maintain dat A. The analytical data store performs poorly. You must implement a solution that meets the following requirements: Provide data warehousing Reduce ongoing management activities Deliver SQL query responses in less than one second You need to create an HDInsight cluster to meet the requirements. Which type of cluster should you create
Computers and Technology
1 answer:
eduard3 years ago
7 0

Answer:

Apache Spark

Explanation:

The user seems to be a system technician who applies the lambda architecture with Microsoft Azure. using the open-source Big Data system to store, analyze, as well as manage information. Analytical information storage is not doing well.

It would eventually incorporate the approach that satisfies the following specifications that enable the development of a High definition Insight cluster to satisfy the specifications. So, the Apache Spark cluster type that he would develop.

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Factor f(x)=x^3-6x^2+9x
liq [111]
Since all terms have an x in them, you can first factor that out, yielding:

f(x) = x(x² - 6x + 9)

Then you are looking for numbers that multiplied give 9 and added give -6, which is -3 and -3. So the final factorization is:

f(x) = x(x-3)²

6 0
3 years ago
A cloud service provider uses the Internet to deliver a computing environment for developing, running, and managing software app
MakcuM [25]

The answer is PaaS (Platform as a Service)  

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6 0
3 years ago
"The network layer is responsible for transferring packets of data from the A.Source computer to the destination computer on adj
galben [10]

Answer:

Source computer to the destination computer via one of more networks

Explanation:

The network layer provides the means of transferring variable-length network packets from a source to a destination host via one or more networks.

3 0
3 years ago
When implementing a physical database from a logical data model, you must consider database performance by allowing data in the
Galina-37 [17]

Answer:

A method  used to improve the performance of structure when running queries is known as Partitioning indexes.

The advantages of partitioning indexes are, It enables data management operations for example,  index creation and rebuilding, It increases query performance.

The disadvantages are, one cannot define the primary index of partitioned table to be unique unless the whole partitioning column set is part of the primary index definition.

Explanation:

Solution

Partitioning indexes are known as b -tress indexes that shows hon how to break up the index into separate or different partitions.

Partitioning is usually done to enhance the performance and increased availability. when data are spread over  multiple partitions, one can be able to operate on one partition  without affecting others. i.e to run utilities, or to take data offline.

Almost all DBMS products support partitioning, but in various ways. we must be sure to know the nuances of an individual a particular DBMS execution before partitioning.

The advantages of Partitioned indexes are as follows:

It enables data management operations for example,  index creation and rebuilding

It increases  performance of query

It can significantly the impact of schedule downtime for maintenance operations

Disadvantages:

The primary index of partitioned table cannot be described to be unique except if  the whole partitioning column set is part of the primary index definition.

5 0
4 years ago
Help pleaseeeeeeee !!!
dedylja [7]
I think it’s false but I’m not exactly certain
3 0
3 years ago
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