- What is rack in Kafka?
- What is the difference between Hadoop and traditional Rdbms?
- What is rack in Hadoop?
- What was Hadoop named after?
- Which type of data Hadoop can deal with?
- What is the advantage of MapR?
- What is rack awareness algorithm in Hadoop?
- How do I delete a topic in confluent Kafka?
- What is the first step in a write process from a Hdfs client?
- What is Hadoop architecture?
- What is Hadoop cluster?
- What is the difference between Hadoop 1 and Hadoop 2?
- What is a rack awareness and on what basis is data stored in a rack?
- What is checkpointing in Hadoop?
- Is Hadoop a NoSQL?
- What is Kafka replication factor?
- How does consumer group work in Kafka?
- What is rack in cluster?
What is rack in Kafka?
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 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 rack 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 .
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.
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 the advantage of MapR?
MapR Benefits The main benefits of MapR are its open source engines and tools, its open API and interface, and its real-time streaming. Here are the details: Users of the MapR Converged Data Platform can expect help when it comes to the direct processing of event files, tables, and streams.
What is rack awareness algorithm in Hadoop?
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 I delete a topic in confluent Kafka?
Delete a topicSelect a cluster from the navigation bar.Click the Topics cluster submenu. The Topics page appears.Click the link for the topic name. The Overview page appears.Click the Configuration tab.Click Edit settings -> Delete topic.Confirm the topic deletion by typing the topic name and click Continue.
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 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 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.
What is the difference between Hadoop 1 and Hadoop 2?
In Hadoop 1, there is HDFS which is used for storage and top of it, Map Reduce which works as Resource Management as well as Data Processing. … In Hadoop 2, there is again HDFS which is again used for storage and on the top of HDFS, there is YARN which works as Resource Management.
What is a rack awareness and on what basis is data stored in a rack?
Rack Awareness in Hadoop is the concept that chooses closer Datanodes based on the rack information. By default, Hadoop installation assumes that all the nodes belong to the same rack. … NameNode chooses data nodes, which are on the same rack or a nearby rock to read/ write requests (client node).
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.
Is Hadoop a NoSQL?
Hadoop is not a type of database, but rather a software ecosystem that allows for massively parallel computing. It is an enabler of certain types NoSQL distributed databases (such as HBase), which can allow for data to be spread across thousands of servers with little reduction in performance.
What is Kafka replication factor?
A replication factor is the number of copies of data over multiple brokers. … The replication factor value should be greater than 1 always (between 2 or 3). This helps to store a replica of the data in another broker from where the user can access it.
How does consumer group work in Kafka?
Kafka Consumer Groups You group consumers into a consumer group by use case or function of the group. … Each consumer group is a subscriber to one or more Kafka topics. Each consumer group maintains its offset per topic partition. If you need multiple subscribers, then you have multiple consumer groups.
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.