Writing and Reading Data in HDFS
In this tutorial, generate random data and write them to HDFS. Then, read the data from HDFS, sort them and display the result in the Console.
Watch NowIn this tutorial, generate random data and write them to HDFS. Then, read the data from HDFS, sort them and display the result in the Console.
Watch NowIn this tutorial, create Hadoop Cluster metadata by importing the configuration from the Hadoop configuration files.
This tutorial uses Talend Data Fabric Studio version 6 and a Hadoop cluster: Cloudera CDH version 5.4.
1. Create a new Hadoop cluster metadata definition
Ensure that the Integration perspective is selected.
In the Project Repository, expand Metadata, right-click Hadoop Cluster, and click Create Hadoop Cluster to open the wizard.
In the Name field of the Hadoop Cluster Connection wizard, type MyHadoopCluster_files. In the Purpose field, type Cluster connection metadata, in the Description field, type Metadata to connect to a Cloudera CDH 5.4 cluster, and click Next.
Learn how to create Hadoop Cluster metadata automatically by connecting to the Cloudera Manager.
Watch NowIn this tutorial, create a Big Data batch Job running on YARN, read data from HDFS, sort them and display them in the Console.
Watch NowLearn how to create a Big Data batch Job using the Spark framework, read data from HDFS, sort them and display them in the Console.
Watch NowThis white paper shows you what is a data hub and why are the most forward-looking companies creating them.
Download NowApache Sqoop is an instrument expressly designed to import and export structured data into and out of Hadoop and repositories like relational databases, data warehouses, and NoSQL stores.
View NowData extraction tools significantly expedite the collection of relevant data. Learn about the tool and the benefits achieved by leveraging the right data extraction software.
View NowA good data quality solution empowers you to readily embrace enterprise-class data governance as a core discipline within your data management processes, simply and effectively.
Watch NowWith 50% of business data residing in the cloud, more organizations are turning to ELT tools to address their processing needs. Learn how ELT tools are impacting the future of data integration.
View NowThis Multiplatform Data Architectures report explains in detail what MDAs are and do, with a focus on helping data professionals and their business counterparts worldwide architect, govern, and grow their MDAs for better business outcomes via well-integrated and unified distributed data from many sources.
Download NowSince the dawn of big data, the ETL (extract, transform, and load) process has been the heart that pumps information through modern business networks. Today, cloud-based ETL is a critical tool for managing massive data sets, and one that companies will increasingly rely on in the future.
View NowLearn how to extract CRM data from Salesforce and load it into the Amazon Web Services (AWS) Redshift cloud data warehouse.
View NowELT is the process by which raw data is extracted, loaded, and transformed into a data lake or warehouse. In contrast to ETL, ELT provides faster loading.
View NowMapReduce is a programming model or pattern within the Hadoop framework that is used to access big data stored in the Hadoop File System (HDFS). The map function takes input, pairs, processes, and produces another set of intermediate pairs as output.
View NowETL testing refers to tests applied throughout the ETL process to validate, verify, and ensure the accuracy of data while preventing duplicate records and data loss. Learn the 8 stages of ETL testing, 9 types of tests, common challenges, how to find the best tool, and more.
View NowHadoop is an open source, Java based framework used for storing and processing big data. The data is stored on inexpensive commodity servers that run as clusters. Its distributed file system enables concurrent processing and fault tolerance.
View NowWith the advent of big data, data quality management is both more important and more challenging than ever. Fortunately the combination of Hadoop open source distributed processing technologies and Talend open source data management solutions bring big data quality operations within the reach of any organization.
View NowThe difference between ETL and ELT lies in where data is transformed into business intelligence and how much data is retained in working data warehouses. Discover what those differences mean for business intelligence, which approach is best for your organization, and why the cloud is changing everything.
View NowThe recent introduction of YARN in Hadoop provides organizations that are managing big data with even greater processing speed and scalability. An acronym for Yet Another Resource Negotiator, YARN in Hadoop solves a bottleneck in the first version of Hadoop MapReduce and reduces the strict dependency of Hadoop environments on MapReduce.
View NowYARN in Hadoop provides a new processing platform for big data that is not constrained to MapReduce. Also known as MapReduce 2.0, YARN decouples the resource management and scheduling capabilities from the data processing component in Hadoop, limiting the dependency of Hadoop environments on the MapReduce program.
View NowThe market for data warehouse tools and other integration technologies is shifting in favor of open source solutions. Talend is at the forefront of this movement, providing progressive businesses with open source data warehouse tools that deliver as much or more quality and functionality as proprietary solutions, while having substantially lower total cost of ownership.
View NowTalend, the open source integration company, delivers seamless Hadoop Hive support in Talend Open Studio for Big Data. The first pure open source big data management solution, Talend Open Studio for Big Data makes it easy to work with Hadoop Hive and to integrate Hive into your enterprise data flows.
View NowBig data integration is a key operational challenge for today's enterprise IT departments. Talend, the leading provider of open source data management solutions, helps organizations large and small meet the big data challenge by making big data integration easy, fast, and affordable.
View Now