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Hortonworks Apache-Hadoop-Developer 試験シラバストピック:

Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer 認定 Apache-Hadoop-Developer 試験問題：

1. For each intermediate key, each reducer task can emit:

A) As many final key-value pairs as desired. There are no restrictions on the types of those key-value pairs (i.e., they can be heterogeneous).
B) As many final key-value pairs as desired, as long as all the keys have the same type and all the values have the same type.
C) One final key-value pair per key; no restrictions on the type.
D) One final key-value pair per value associated with the key; no restrictions on the type.
E) As many final key-value pairs as desired, but they must have the same type as the intermediate key-value pairs.

2. You want to count the number of occurrences for each unique word in the supplied input data. You've decided to implement this by having your mapper tokenize each word and emit a literal value 1, and then have your reducer increment a counter for each literal 1 it
receives. After successful implementing this, it occurs to you that you could optimize this by specifying a combiner. Will you be able to reuse your existing Reduces as your combiner in this case and why or why not?

A) No, because the sum operation in the reducer is incompatible with the operation of a Combiner.
B) Yes, because the sum operation is both associative and commutative and the input and output types to the reduce method match.
C) No, because the Combiner is incompatible with a mapper which doesn't use the same data type for both the key and value.
D) No, because the Reducer and Combiner are separate interfaces.
E) Yes, because Java is a polymorphic object-oriented language and thus reducer code can be reused as a combiner.

3. Which one of the following classes would a Pig command use to store data in a table defined in HCatalog?

A) Pig scripts cannot use an HCatalog table
B) org.apache.hcatalog.pig.HCatOutputFormat
C) No special class is needed for a Pig script to store data in an HCatalog table
D) org.apache.hcatalog.pig.HCatStorer

4. Which project gives you a distributed, Scalable, data store that allows you random, realtime read/write access to hundreds of terabytes of data?

A) HBase
B) Pig
C) Hive
D) Sqoop
E) Hue
F) Flume
G) Oozie

5. Which one of the following statements is true about a Hive-managed table?

A) Hive dynamically defines the schema of the table based on the format of the underlying data.
B) Records can only be added to the table using the Hive INSERT command.
C) When the table is dropped, the underlying folder in HDFS is deleted.
D) Hive dynamically defines the schema of the table based on the FROM clause of a SELECT query.

質問と回答：