adplus-dvertising
frame-decoration

Question

How does sideways cracking address the problem of misalignment in column-store systems when working with multiple columns of the same table?

a.

It cracks all columns of the same table in the same way.

b.

It performs random access for tuple reconstruction.

c.

It works on pairs of columns at a time and forwards cracking actions across columns.

d.

It uses bit vectors to align columns.

Posted under Big Data Computing

Answer: (c).It works on pairs of columns at a time and forwards cracking actions across columns. Explanation:Sideways cracking addresses the problem of misalignment in column-store systems when working with multiple columns of the same table by working on pairs of columns at a time and forwarding cracking actions across columns.

Engage with the Community - Add Your Comment

Confused About the Answer? Ask for Details Here.

Know the Explanation? Add it Here.

Q. How does sideways cracking address the problem of misalignment in column-store systems when working with multiple columns of the same table?

Similar Questions

Discover Related MCQs

Q. How does sideways cracking ensure alignment of column-pairs with the same head attribute?

Q. What is the benefit of sideways cracking in column-store systems when multiple columns of the same table are used in a query?

Q. What is the purpose of partial cracking in column-store systems?

Q. How does partial cracking manage storage space for cracking columns?

Q. How does cracking handle updates to the data?

Q. What is the purpose of the auxiliary delete and insert columns in cracking?

Q. How does cracking manage merging pending updates into cracking columns?

Q. What is the primary motivation for the introduction of adaptive merging as a complementary technique to cracking?

Q. How are data handled in adaptive merging after they are sorted in memory with a quicksort action?

Q. What happens if a query in adaptive merging is fully covered by the results column?

Q. How does adaptive merging improve over plain cracking in terms of convergence speed?

Q. What is the main advantage of the crack-sort hybrid compared to other hybrid algorithms?

Q. How does the performance of cracking depend on the arrival order of queries?

Q. What problem does stochastic cracking aim to solve?

Q. How does stochastic cracking work to reduce the chances of leaving back big uncracked pieces?

Q. Why is concurrent access to data challenging in the context of database cracking?

Q. How does database cracking achieve concurrency control for adaptive indexing during read queries?

Q. In the context of adaptive indexing during read queries, what remains intact even when data organization changes?

Q. What is the advantage of using latching for concurrency control in adaptive indexing?

Q. Why is data loading considered a necessary step when setting up a database system?