article thumbnail

Top 6 Microsoft HDFS Interview Questions

Analytics Vidhya

Introduction Microsoft Azure HDInsight(or Microsoft HDFS) is a cloud-based Hadoop Distributed File System version. HDInsight works seamlessly with the Hadoop ecosystem, which includes technologies like MapReduce, Hive, […] The post Top 6 Microsoft HDFS Interview Questions appeared first on Analytics Vidhya.

Hadoop 313
article thumbnail

Unfolding the Details of Hive in Hadoop

Pickl AI

Here comes the role of Hive in Hadoop. Hive is a powerful data warehousing infrastructure that provides an interface for querying and analyzing large datasets stored in Hadoop. In this blog, we will explore the key aspects of Hive Hadoop. What is Hadoop ? Hive is a data warehousing infrastructure built on top of Hadoop.

Hadoop 52
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Azure Data Engineer Jobs

Pickl AI

Accordingly, one of the most demanding roles is that of Azure Data Engineer Jobs that you might be interested in. The following blog will help you know about the Azure Data Engineering Job Description, salary, and certification course. How to Become an Azure Data Engineer?

Azure 52
article thumbnail

Cloud Data Science 10

Data Science 101

Azure HDInsight now supports Apache analytics projects This announcement includes Spark, Hadoop, and Kafka. The frameworks in Azure will now have better security, performance, and monitoring. The first course in the Mastering Azure Machine Learning sequence has been released. I might have to join in the future.

article thumbnail

Was ist ein Data Lakehouse?

Data Science Blog

Data Lakehouses werden auf Cloud-basierten Objektspeichern wie Amazon S3 , Google Cloud Storage oder Azure Blob Storage aufgebaut. Spark ist direkt auf mehreren Cloud-Plattformen verfügbar, darunter AWS, Azure und Google Cloud Platform.Apacke Spark ist jedoch mehr als nur ein Tool, es ist die Grundbasis für die meisten anderen Tools.

article thumbnail

Becoming a Data Engineer: 7 Tips to Take Your Career to the Next Level

Data Science Connect

Familiarize yourself with essential data technologies: Data engineers often work with large, complex data sets, and it’s important to be familiar with technologies like Hadoop, Spark, and Hive that can help you process and analyze this data.

article thumbnail

Data Warehouse vs. Data Lake

Precisely

Hadoop, Snowflake, Databricks and other products have rapidly gained adoption. We will also address some of the key distinctions between platforms like Hadoop and Snowflake, which have emerged as valuable tools in the quest to process and analyze ever larger volumes of structured, semi-structured, and unstructured data.