Language Support

5 minutes 5 Questions

Amazon CloudSearch provides support for multiple languages through its powerful text processing features. Built-in language-specific text analyzers allow the service to accurately interpret and index content in several languages, including English, French, German, Italian, Portuguese, and Spanish. Additionally, language-specific stemming and stopword lists are available, enabling users to optimize search results for their target audience. Furthermore, Amazon CloudSearch supports Unicode character sets, making it possible to index content in numerous writing systems.

Guide on Language Support in Amazon CloudSearch

What it is:
Amazon CloudSearch Language Support is a feature that enables analyzing and indexing of text in multiple languages. It supports a multitude of languages including English, Spanish, French, German, Italian, Chinese, Japanese, Korean, etc.

Why it is Important:
Understanding the language support in AWS CloudSearch is crucial to design and architect AWS solutions for international and multilingual applications. Without language support, the data cannot be efficiently indexed or searched which can negatively impact system performance and user experience.

How it Works
When you configure an Amazon CloudSearch domain to support a particular language, the text processing options such as tokenization, stopwords, stemming, etc., are tailored according to the language-specific characteristics. This enables AWS CloudSearch to analyze and interpret the text accurately in the specified language.

Exam Tips: Answering Questions on Language Support:
For the exam, be sure to understand how to use language-specific text processing options in AWS CloudSearch. Remember the range of supported languages and how they are structured for index fields.
Also understand the role of Analysis schemes (which include a tokenizer and a stemmer, stopwords, synonyms, etc.) and their important role in text processing.
The exam may also include questions on how the correct language support can impact search relevance and accuracy. Understanding the implications of language support on the broader AWS solution design is critical to answer these questions effectively.

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Question 1

An e-commerce company uses AWS Lambda to run its backend services. They want to expand their support to international customers and need to localize their processing in different languages. Which Lambda runtime(s) should they use?

Only Java Only Node.js Node.js, Python, or Java Only Python

Correct Answer: Node.js, Python, or Java

AWS Lambda runtimes, like Node.js, Python, and Java offer extensive libraries for internationalization (i18n) and localization (l10n) support. Choosing any of these languages will provide the required support for their international customers. Ruby and Go are not recommended for this use case as their localization features might be limited compared to the suggested runtimes.

Question 2

A team needs to create an application with different language combinations supported by the Amazon Lex bot. What language combination is NOT supported by Amazon Lex?

English and Chinese English and Spanish Japanese and Russian English and French

Correct Answer: Japanese and Russian

As of now, Amazon Lex does not support Japanese and Russian language combinations. Other mentioned combinations like English with Spanish, Chinese, French, Italian, or Korean are supported by Lex.

Question 3

A company is migrating their Node.js application to AWS Lambda. The application currently uses a C++ library for intensive computation. What is the best approach for the migration?

Directly uploading the Node.js application with the C++ library Creating an AWS Lambda layer with the required Node.js and C++ files Using Amazon Elastic Beanstalk for the migration Uploading the application to Amazon S3

Correct Answer: Creating an AWS Lambda layer with the required Node.js and C++ files

The correct solution is to create an AWS Lambda layer with the required Node.js and C++ files. This will allow the application to use AWS Lambda's native tooling for language support, as well as preserving the critical elements of the C++ library. Directly uploading or installing the library is not recommended, and solutions like Amazon Elastic Beanstalk and Amazon S3 are not suitable for this case.

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