READ Free Dumps For Cloudera- CCD-410
| Question ID 12501 | What data does a Reducer reduce method process?
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| Option A | All the data in a single input file.
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| Option B | All data produced by a single mapper.
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| Option C | All data for a given key, regardless of which mapper(s) produced it.
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| Option D | All data for a given value, regardless of which mapper(s) produced it.
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| Correct Answer | C |
Explanation Explanation: Reducing lets you aggregate values together. A reducer function receives an iterator of input values from an input list. It then combines these values together, returning a single output value. All values with the same key are presented to a single reduce task. Reference: Yahoo! Hadoop Tutorial, Module 4: MapReduce
| Question ID 12502 | Table metadata in Hive is:
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| Option A | Stored as metadata on the NameNode.
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| Option B | Stored along with the data in HDFS.
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| Option C | Stored in the Metastore.
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| Option D | Stored in ZooKeeper.
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| Correct Answer | C |
Explanation Explanation: By default, hive use an embedded Derby database to store metadata information. The metastore is the "glue" between Hive and HDFS. It tells Hive where your data files live in HDFS, what type of data they contain, what tables they belong to, etc. The Metastore is an application that runs on an RDBMS and uses an open source ORM layer called DataNucleus, to convert object representations into a relational schema and vice versa. They chose this approach as opposed to storing this information in hdfs as they need the Metastore to be very low latency. The DataNucleus layer allows them to plugin many different RDBMS technologies. Note: * By default, Hive stores metadata in an embedded Apache Derby database, and other client/server databases like MySQL can optionally be used. * features of Hive include: Metadata storage in an RDBMS, significantly reducing the time to perform semantic checks during query execution. Reference: Store Hive Metadata into RDBMS