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Huawei H13-723-ENU Exam Syllabus Topics:

Huawei HCIP-Big Data Developer Sample Questions:

1. Regarding FusionInsight HD's Spark, which of the following programming languages can be used to develop Spark applications? (multiple choice)

A) Scala
B) C
C) Python
D) Java

2. Use FusionInsight HD's Hive to query data. When the amount of intermediate result data to be queried is large, you can choose to compress the intermediate result data to obtain better performance.
Which of the following are the relevant parameters for Hive intermediate result compression? (multiple choice)

A) hive.intermediate.compression.type
B) hive.intermediate.compression.codec
C) hive.exec.compress.intermediate
D) hive.exec.compress.output

3. When Flume writes into HDFS, what are the file generation methods? (multiple choice)

A) Set the number of events stored in a single file. When the number of events stored in the file reaches the set value, the old file will be closed and the new data will be written to the new file
B) Set the file generation time interval. When the time interval is reached, the old file will be closed and the new data will be written into the new file
C) Set the size of a single file. When the file size reaches the set value, the old file will be closed and the new data will be written into the new file
D) According to the source file name, directly generate the file

4. Which of the following scenarios is not suitable for Redis? (multiple choice)

A) Counter application: for example, counting the number of people logged in to a certain website
B) Get the latest N data: for example, get the latest 10 comments on a Weibo
C) Complex transaction operations
D) A message queue application that is consumed by multiple consumers at the same time and guarantees that the message is successfully consumed by all subscribers (subscription-notification)

5. When indexing in Solr, which of the following code snippets can significantly improve indexing performance? (multiple choice)

A) if (updateRequest.getDocumentsMap().size() >= 10000) { cloudSolrClient.request (updateRequest, collName); updateRequest.clear(); }
B) if (updateRequest.getDocuments().size() >= 1000) { cloudSolrClient.request (updateRequest, collName); updateRequest.clear(); }
C) SolrlnputDocument doc = new SolrlnputDocument(); doc.addField ("id", i.toString()); doc.addField ("name", "Zhang San" + i); doc.addField ("features", "test" + ); doc.addField ("price", (float) i * 1.01); cloudSolrClient.add (doc); cloudSolrClient.commit();
D) lbClient.setRequestWriter (new BinaryRequestWriter());

Solutions: