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NEW QUESTION: 1
You observe that the number of spilled records from map tasks for exceeds the number of map output records. You child heap size is 1 GB and your io.sort.mb value is set to 100MB. How would you tune your io.sort.mb value to achieve maximum memory to disk I/O ratio?
A. For 1GB child heap size an io.sort.mb of 128MB will always maximum memory to disk I/O.
B. Tune io.sort.mb value until you observe that the number of spilled records equals (or is as close to equals) the number of map output records.
C. Decrease the io.sort.mb value below 100M
D. Increase the IO.sort.mb as high you can, as close to 1GB as possible.
Answer: B
Explanation:
here are a few tradeoffs to consider.
1.the number of seeks being done when merging files. If you increase the merge factor too high, then the seek cost on disk will exceed the savings from doing a parallel merge (note that OS cache might mitigate this somewhat).
2.Increasing the sort factor decreases the amount of data in each partition. I believe the number is io.sort.mb / io.sort.factor for each partition of sorted data. I believe the general rule of thumb is to have io.sort.mb = 10 * io.sort.factor (this is based on the seek latency of the disk on the transfer speed, I believe. I'm sure this could be tuned better if it was your bottleneck. If you keep these in line with each other, then the seek overhead from merging should be minimized
3.you increase io.sort.mb, then you increase memory pressure on the cluster, leaving less memory available for job tasks. Memory usage for sorting is mapper tasks * io.sort.mb -- so you could find yourself causing extra GCs if this is too high
Essentially,
If you find yourself swapping heavily, then there's a good chance you have set the sort factor too high.
If the ratio between io.sort.mb and io.sort.factor isn't correct, then you may need to change io.sort.mb (if you have the memory) or lower the sort factor.
If you find that you are spending more time in your mappers than in your reducers, then you may want to increase the number of map tasks and decrease the sort factor (assuming there is memory pressure).
Reference: How could I tell if my hadoop config parameter io.sort.factor is too small or too big?
http://stackoverflow.com/questions/8642566/how-could-i-tell-if-my-hadoop-config-parameter-iosort-factor-is-too-small-or-to

NEW QUESTION: 2
開発チームのメンバーは、サードパーティのシステムとの統合を含む、優先順位付けされた非機能要件に取り組んでいます。この統合は、以前はプロジェクトで行われていませんでした。
プロジェクトリーダーは何を提案すべきですか？
A. 実装アプローチを開発およびテストし、フィードバックを収集するために次のスプリントレビューで実証します。
B. 詳細なアーキテクチャ設計の開発と文書化、開発チームとのピアレビュー、および実装/テスト
C. ソリューションの機能要件を、非機能要件よりも先に開発します。これにより、顧客価値が向上します。
D. 統合要件を製品の所有者と話し合い、バックログで低くなるように交渉して、最小限の市場性のある機能に焦点を当てます
Answer: B

NEW QUESTION: 3

A. Option C
B. Option D
C. Option A
D. Option B
Answer: B

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