Data Distribution Strategy for a 1 GB Table
Question
As a data consultant of a famous Internet services company, you are assigned a new challenge to design a SATA solution for the following scenario.
There is a table which has a size of 1 GB.
There is no common join key with other tables.
You have to choose a data distribution strategy considering these needs.
Choose the most suitable option from the table which tells about the right strategy.
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B. C. D.Correct Answer: A.
This question has two main pointers which will lead to the correct answer.
The first says that the table size is less than 2 GB and is 1 GB.
The second one says that there is no possible join key.
Round Robin is a suggested method in scenarios where there is no obvious joining key.
As per the question, we don't have a common joining key.
The following shows the places where Round Robin can be used.
When there is no eligible column for hash distributing the table.
When there are no common join keys.
If the stable is for staging purpose.
Option A is correct: It will meet the requirements.
Option B is incorrect: It is used when there is a common join key, and table size is more than 2 GB.Option C is incorrect: Its main purpose is to group into fragments, and it is not a distribution technique.
Option D is incorrect:
Option A is the right answer.
To know more about Distribution methods, please refer to the doc below:
Sure, I can explain the different data distribution strategies and suggest the most suitable option for the given scenario.
Data distribution is a crucial aspect of designing a scalable and efficient data storage solution. In a distributed database system, data can be distributed across multiple nodes or partitions to ensure high availability, fault tolerance, and parallel processing.
The following are the common data distribution strategies used in distributed database systems:
Round Robin: In this strategy, data is distributed evenly across all available nodes or partitions in a circular manner. Each row of data is assigned to the next node in the sequence. Round Robin is a simple and efficient data distribution strategy that ensures even distribution of data, but it does not consider the content of the data.
Hash Distributed: In this strategy, a hash function is applied to a specific column of the table to determine the partition or node to which a row of data belongs. The hash function ensures that rows with the same value in the selected column are assigned to the same partition, which facilitates efficient querying and joins. Hash distribution is a widely used strategy for large tables in distributed systems.
Vertical Fragmentation: In this strategy, columns of a table are partitioned and distributed across different nodes or partitions based on their access patterns or usage. This strategy is suitable for tables with a large number of columns, and it can reduce data duplication and improve query performance for specific queries.
Based on the given scenario, where there is a single table of 1 GB size with no common join key with other tables, the most suitable data distribution strategy is Hash Distributed. This strategy can distribute the rows of the table across multiple nodes or partitions based on the hash value of a selected column, which can improve query performance and enable efficient querying and joins.
Round Robin strategy may also be suitable, but it does not consider the content of the data, and it may not provide efficient querying or joins. Vertical Fragmentation is not suitable for the given scenario, as there is only one table with no common join key with other tables.
Therefore, the correct answer is B. Hash Distributed.
