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NEW QUESTION: 1
どのプログラミング言語に対応するIBM Watson SDKがありますか?
A. C++
B. Perl
C. Python
D. Julia
Answer: C
Explanation:
Explanation
Reference https://cloud.ibm.com/docs/services/watson?topic=watson-using-sdks
NEW QUESTION: 2
Which two statements are true about Java Cryptography Architecture (JCA)?
A. Implementations of cryptographic algorithms can be plugged in to a JVM after it has been installed and at run time.
B. Categories of algorithms supported by JCA include message digests, signatures encryption, management, and random number generation.
C. Exactly one Implementation of each category of cryptographic algorithms must be provided.
D. Any JCA provider must implement each supported category of algorithms.
Answer: A,B
NEW QUESTION: 3
企業は、開発者がコードを共有および比較できるようにするアプリケーションを構築します。 アプリケーション内のユーザーが共有する会話、コードスニペット、およびリンクは、Microsoft Azure SQL Databaseインスタンスに保存されます。
このアプリケーションでは、過去の会話とコードスニペットを検索できます。
ユーザーがコードスニペットを共有すると、SUBSTRING、FIRST_VALUE、SQRTなどのTransact-SQL関数の組み合わせを使用して、コードスニペットが以前に共有されたコードスニペットと比較されます。 一致が見つかった場合、一致へのリンクが会話に追加されます。
お客様から次の問題が報告されています。
* Delays occur during live conversations
* A delay occurs before matching links appear after code snippets are added to conversations You need to resolve the performance issues.
Which technologies should you use? To answer, drag the appropriate technologies to the correct issues. Each technology may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: memory-optimized table
In-Memory OLTP can provide great performance benefits for transaction processing, data ingestion, and transient data scenarios.
Box 2: materialized view
To support efficient querying, a common solution is to generate, in advance, a view that materializes the data in a format suited to the required results set. The Materialized View pattern describes generating prepopulated views of data in environments where the source data isn't in a suitable format for querying, where generating a suitable query is difficult, or where query performance is poor due to the nature of the data or the data store.
These materialized views, which only contain data required by a query, allow applications to quickly obtain the information they need. In addition to joining tables or combining data entities, materialized views can include the current values of calculated columns or data items, the results of combining values or executing transformations on the data items, and values specified as part of the query. A materialized view can even be optimized for just a single query.
References:
https://docs.microsoft.com/en-us/azure/architecture/patterns/materialized-view