ProjectPro
JUNE 6, 2025
Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc. Thus, having worked on projects that use tools like Apache Spark, Apache Hadoop , Apache Hive, etc., Experience with using cloud services providing platforms like AWS/GCP/Azure. and their implementation on the cloud is a must for data engineers.
ProjectPro
MAY 2, 2016
News on Hadoop-April 2016 Cutting says Hadoop is not at its peak but at its starting stages. Datanami.com At his keynote address in San Jose, Strata+Hadoop World 2016, Doug Cutting said that Hadoop is not at its peak and not going to phase out. Source: [link] ) Dr. Elephant will now solve your Hadoop flow problems.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
ProjectPro
JUNE 6, 2025
Introduced by Facebook in 2009, it brought structure to chaos and allowed SQL access to Hadoop data. It’s particularly useful when organizations need to: Migrate from legacy Hadoop-based lakes to cloud-native architectures. config("spark.sql.catalog.my_catalog.type", "hadoop").config("spark.sql.catalog.my_catalog.warehouse",
ProjectPro
FEBRUARY 10, 2016
It is difficult to believe that the first Hadoop cluster was put into production at Yahoo, 10 years ago, on January 28 th , 2006. Ten years ago nobody was aware that an open source technology, like Apache Hadoop will fire a revolution in the world of big data. Happy Birthday Hadoop With more than 1.7
Knowledge Hut
MAY 2, 2024
Market Demands for Spark and MapReduce Apache Spark was originally developed in 2009 at UC Berkeley by the team who later founded Databricks. Compatibility MapReduce is also compatible with all data sources and file formats Hadoop supports. It is not mandatory to use Hadoop for Spark, it can be used with S3 or Cassandra also.
ProjectPro
MARCH 23, 2015
In one of our previous articles we had discussed about Hadoop 2.0 YARN framework and how the responsibility of managing the Hadoop cluster is shifting from MapReduce towards YARN. In one of our previous articles we had discussed about Hadoop 2.0 Here we will highlight the feature - high availability in Hadoop 2.0
Data Science Blog: Data Engineering
JULY 4, 2022
Apache Spark began as a research project at UC Berkeley’s AMPLab, a student, researcher, and faculty collaboration centered on data-intensive application domains, in 2009. Spark outperforms Hadoop in many ways, reaching performance levels that are nearly 100 times higher in some cases.
Expert insights. Personalized for you.
94 
Let's personalize your content