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Huawei HCIP-Big Data Developer V1.0 Sample Questions:

1. In FusionInsight HD, use the Streaming command line to submit the om.huawei.examole.WordCount task in example.jar. The task name is wcTest. Which of the following commands is correct?

A) storm jar example .jar om.huawei.example.WordCount wcTest
B) storm jar example.jar WordCount wcTest
C) storm jar example .jar wcTest om.huawei.example.WordCount
D) storm jar example .jar wcTest WordCount

2. Which of the following measures can improve the query performance of HBase? (multiple choice)

A) The data read at the same time are stored in the same cell
B) Query frequent attributes are placed in front of rowkey
C) Use secondary indexes to adapt to more query scenarios
D) Pre-divide regions to make regions evenly distributed and improve concurrency

3. The calculation logic of the Spark application will be parsed into DNG. Which of the following functional modules will complete this parsing operation?

A) Executor
B) Application Master
C) Driver
D) Client

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

A) 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
B) According to the source file name, directly generate the file
C) 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
D) 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

5. In Spark application development, which of the following codes can correctly count words?

A) val counts = textFile.flatMap (line=>line.split (" ")).map (word => (word, 1)).groupByKey ()
B) val counts = textFile.flatMap (line=>line.split (" ")).map (word => (word, 1)).reduceByKey(_ +_)
C) val counts = textFile.map (line => line.split ("')).map (-rd => (word, 1)).reduceByKey(_ +_)
D) val counts = textFile.map (line=>line.split (" ")).map (word => (word, 1)).groupByKey ()

Solutions: