Hadoop Interview Questions and Answers Set 4

31. Explain what is difference between an Input Split and HDFS Block?

Logical division of data is known as Split while physical division of data is known as HDFS Block.


32. How can native libraries be included in YARN jobs?

There are two ways to include native libraries in YARN jobs-

1)  By setting the -Djava.library.path on the command line  but in this case there are chances that the native libraries might not be loaded correctly and there is possibility of errors.

2) The better option to include native libraries is to the set the LD_LIBRARY_PATH in the .bashrc file.

33. What is Apache HBase?

HBase is an open source, multidimensional, distributed, scalable and a NoSQL database written in Java. HBase runs on top of HDFS (Hadoop Distributed File System) and provides BigTable (Google) like capabilities to Hadoop. It is designed to provide a fault tolerant way of storing large collection of sparse data sets. HBase achieves high throughput and low latency by providing faster Read/Write Access on huge data sets.

34. What is “SerDe” in “Hive”?

Apache Hive is a data warehouse system built on top of Hadoop and is used for analyzing structured and semi-structured data developed by Facebook. Hive abstracts the complexity of Hadoop MapReduce.

The “SerDe” interface allows you to instruct “Hive” about how a record should be processed. A “SerDe” is a combination of a “Serializer” and a “Deserializer”. “Hive” uses “SerDe” (and “FileFormat”) to read and write the table’s row.

35. Explain “WAL” in HBase?

Write Ahead Log (WAL) is a file attached to every Region Server inside the distributed environment. The WAL stores the new data that hasn’t been persisted or committed to the permanent storage. It is used in case of failure to recover the data sets.

Weekend / Weekday Batch

36. What is Apache Spark?

The answer to this question is, Apache Spark is a framework for real time data analytics in a distributed computing environment. It executes in-memory computations to increase the speed of data processing.

It is 100x faster than MapReduce for large scale data processing by exploiting in-memory computations and other optimizations.

37. What is a UDF?

If some functions are unavailable in built-in operators, we can programmatically create User Defined Functions (UDF) to bring those functionalities using other languages like Java, Python, Ruby, etc. and embed it in Script file.

38. Explain about the SMB Join in Hive.

In SMB join in Hive, each mapper reads a bucket from the first table and the corresponding bucket from the second table and then a merge sort join is performed. Sort Merge Bucket (SMB) join in hive is mainly used as there is no limit on file or partition or table join. SMB join can best be used when the tables are large. In SMB join the columns are bucketed and sorted using the join columns. All tables should have the same number of buckets in SMB join.

39. How can you connect an application, if you run Hive as a server?

When running Hive as a server, the application can be connected in one of the 3 ways-

ODBC Driver-This supports the ODBC protocol

JDBC Driver- This supports the JDBC protocol

Thrift Client- This client can be used to make calls to all hive commands using different programming language like PHP, Python, Java, C++ and Ruby.

40. Is YARN a replacement of Hadoop MapReduce?

YARN is not a replacement of Hadoop but it is a more powerful and efficient technology that supports MapReduce and is also referred to as Hadoop 2.0 or MapReduce 2.

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