- What is Hadoop cluster?
- Which type of data Hadoop can deal with?
- What is rack awareness algorithm?
- What are the goals of HDFS?
- What are the key features of HDFS?
- What are the components of HDFS?
- What is checkpointing in Hadoop?
- What is the difference between Hadoop and traditional Rdbms?
- What is Hadoop architecture?
- What is HDFS block in Hadoop?
- What is rack in cluster?
- What was Hadoop named after?
- What is rack in Kafka?
- What is rack awareness in HDFS?
- How do you define rack awareness in Hadoop?
- Where is Hdfs used?
- What is the first step in a write process from a Hdfs client?
- What is name node in Hadoop?
What is Hadoop cluster?
A Hadoop cluster is a collection of computers, known as nodes, that are networked together to perform these kinds of parallel computations on big data sets..
Which type of data Hadoop can deal with?
Hadoop can handle not only structured data that fits well into relational tables and arrays but also unstructured data. A partial list of this type of data Hadoop can deal with are: Computer logs.
What is rack awareness algorithm?
Rack Awareness in Hadoop is the concept that chooses closer Datanodes based on the rack information. … To improve network traffic while reading/writing HDFS files in large clusters of Hadoop. NameNode chooses data nodes, which are on the same rack or a nearby rock to read/ write requests (client node).
What are the goals of HDFS?
The goals of HDFSFast recovery from hardware failures. Because one HDFS instance may consist of thousands of servers, failure of at least one server is inevitable. … Access to streaming data. … Accommodation of large data sets. … Portability.
What are the key features of HDFS?
The key features of HDFS are:Cost-effective: … Large Datasets/ Variety and volume of data. … Replication. … Fault Tolerance and reliability. … High Availability. … Scalability. … Data Integrity. … High Throughput.More items…
What are the components of HDFS?
Hadoop HDFS There are two components of HDFS – name node and data node. While there is only one name node, there can be multiple data nodes. HDFS is specially designed for storing huge datasets in commodity hardware.
What is checkpointing in Hadoop?
Checkpointing is a process that takes an fsimage and edit log and compacts them into a new fsimage. This way, instead of replaying a potentially unbounded edit log, the NameNode can load the final in-memory state directly from the fsimage. This is a far more efficient operation and reduces NameNode startup time.
What is the difference between Hadoop and traditional Rdbms?
Unlike RDBMS, Hadoop is not a database, but rather a distributed file system that can store and process a massive amount of data clusters across computers. However, RDBMS is a structured database approach in which data is stored in rows and columns which can be updated with SQL and presented in different tables.
What is Hadoop architecture?
The Hadoop architecture is a package of the file system, MapReduce engine and the HDFS (Hadoop Distributed File System). The MapReduce engine can be MapReduce/MR1 or YARN/MR2. A Hadoop cluster consists of a single master and multiple slave nodes.
What is HDFS block in Hadoop?
Hadoop HDFS split large files into small chunks known as Blocks. Block is the physical representation of data. It contains a minimum amount of data that can be read or write. HDFS stores each file as blocks. HDFS client doesn’t have any control on the block like block location, Namenode decides all such things.
What is rack in cluster?
The rack is a physical collection of nodes in our Hadoop cluster (maybe 30 to 40). … A rack can have multiple data nodes storing the file blocks and their replica’s. The Hadoop itself is so smart that it will automatically write a particular file block in 2 different Data nodes in Rack.
What was Hadoop named after?
What was Hadoop named after? Explanation: Doug Cutting, Hadoop creator, named the framework after his child’s stuffed toy elephant. Explanation: Apache Hadoop is an open-source software framework for distributed storage and distributed processing of Big Data on clusters of commodity hardware. 8.
What is rack in Kafka?
rack=my-rack-id. The rack awareness feature spreads replicas of the same partition across different racks. This extends the guarantees Kafka provides for broker-failure to cover rack-failure, limiting the risk of data loss should all the brokers on a rack fail at once.
What is rack awareness in HDFS?
Rack Awareness enables Hadoop to maximize network bandwidth by favoring the transfer of blocks within racks over transfer between racks. Especially with rack awareness, the YARN is able to optimize MapReduce job performance. It assigns tasks to nodes that are ‘closer’ to their data in terms of network topology.
How do you define rack awareness in Hadoop?
A Rack is a collection nodes usually in 10 of nodes which are closely stored together and all nodes are connected to a same Switch. When an user requests for a read/write in a large cluster of Hadoop in order to improve traffic the namenode chooses a datanode that is closer this is called Rack Awareness .
Where is Hdfs used?
Hadoop is used for storing and processing big data. In Hadoop, data is stored on inexpensive commodity servers that run as clusters. It is a distributed file system that allows concurrent processing and fault tolerance. Hadoop MapReduce programming model is used for faster storage and retrieval of data from its nodes.
What is the first step in a write process from a Hdfs client?
In the first step the client application calls the namenode to initiates the file creation. Remember that, in a later step, HDFS will divide your file content into equal sized blocks, which then are distributed across several datanodes.
What is name node in Hadoop?
The NameNode is the centerpiece of an HDFS file system. It keeps the directory tree of all files in the file system, and tracks where across the cluster the file data is kept. It does not store the data of these files itself. … The NameNode is a Single Point of Failure for the HDFS Cluster.