Table of Contents
- 1 Where objects that are being worked on by Hadoop are stored?
- 2 Which ecosystem component of Hadoop helps processing data on HDFS as if it is Rdbms?
- 3 What is Hadoop and where it is used?
- 4 Is Hadoop real time?
- 5 How is data stored in Hadoop?
- 6 Is MongoDB part of Hadoop ecosystem?
- 7 What type of data Hadoop can deal with?
- 8 How does Hadoop process large volumes of data?
Where objects that are being worked on by Hadoop are stored?
Block is contiguous location on hard-drive in which the HDFS data is stored. The FileSystem stores the data as the collection of blocks. Similarly, the HDFS store each of the file as a block and distribute it over Hadoop cluster.
Which ecosystem component of Hadoop helps processing data on HDFS as if it is Rdbms?
Hadoop MapReduce
Hadoop MapReduce is the core Hadoop ecosystem component which provides data processing. MapReduce is a software framework for easily writing applications that process the vast amount of structured and unstructured data stored in the Hadoop Distributed File system.
How do a Hadoop administrator handle data node crash and scalability of Hadoop system?
In HDFS, replication data is done to solve the problem of data loss in unfavorable conditions like crashing of the node, hardware failure and so on. Scalability – HDFS stores data on multiple nodes in the cluster, when requirement increases we can scale the cluster.
What is Hadoop and where it is used?
Apache Hadoop is an open source framework that is used to efficiently store and process large datasets ranging in size from gigabytes to petabytes of data. Instead of using one large computer to store and process the data, Hadoop allows clustering multiple computers to analyze massive datasets in parallel more quickly.
Is Hadoop real time?
Since Hadoop cannot be used for real time analytics, people explored and developed a new way in which they can use the strength of Hadoop (HDFS) and make the processing real time. So, the industry accepted way is to store the Big Data in HDFS and mount Spark over it.
Is Hadoop an object storage?
Like object storage, Hadoop was also designed as a scale-out architecture on cheap commodity hardware. The Hadoop File System (HDFS) began with the premise that compute should be moved to the data; thus, it was designed to place data on locally attached storage on the compute nodes themselves.
How is data stored in Hadoop?
On a Hadoop cluster, the data within HDFS and the MapReduce system are housed on every machine in the cluster. Data is stored in data blocks on the DataNodes. HDFS replicates those data blocks, usually 128MB in size, and distributes them so they are replicated within multiple nodes across the cluster.
Is MongoDB part of Hadoop ecosystem?
The main component of Hadoop is HDFS, Map Reduce, and YARN. MongoDB: MongoDB is a cross-platform database program that is document-oriented. It is a NoSQL database program and uses JSON documents (Binary-JSON, to be more specific) with the schema. It is primarily designed as a database.
Which type of the data can be imported to HDFS with the help of flume?
Flume only ingests unstructured data or semi-structured data into HDFS. While Sqoop can import as well as export structured data from RDBMS or Enterprise data warehouses to HDFS or vice versa.
What 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: Spatial data/GPS outputs.
How does Hadoop process large volumes of data?
Tools based on the Hadoop framework run on a cluster of machines which allows them to expand to accommodate the required volume of data. Instead of a single storage unit on a single device, with Hadoop, there are multiple storage units across multiple devices.