ProjectPro

MAY 30, 2016

The next in the series of articles highlighting the most commonly asked Hadoop Interview Questions, related to each of the tools in the Hadoop ecosystem is - Hadoop HDFS Interview Questions and Answers. Commonly Asked HDFS Interview Questions and Answers for 2023 1) What is the difference between HDFS and GFS?

Hadoop 40

Hadoop Metadata Big Data Portfolio 40

LinkedIn Engineering

DECEMBER 19, 2023

The historical upgrade system couldn’t adapt to architectural changes like the introduction of an observer namenode (Now handling a massive influx of read requests – 150K QPS – from services such as Trino ), ZKFC auto-failover, HDFS federation , etc. HDFS capacity is less than 85%. No active HDFS alerts are in place.

Big Data 92

Big Data Hadoop Metadata Data 92

LinkedIn Engineering

MARCH 9, 2023

Every day, we upload nearly 30 million dependencies to the Apache Hadoop Distributed File System (HDFS) to run Spark applications. From user perspective, a typical Spark user normally uploads 132,000 dependencies per month, but only 440 of them are unique, which means a same jar could have been uploaded to HDFS 300 (132,000/440) times.

Hadoop 124

Hadoop Machine Learning Designing Data Pipeline 124

Data Engineering Podcast

FEBRUARY 18, 2024

If you've learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com ) with your story. If you've learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com ) with your story.

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

Knowledge Hut

DECEMBER 21, 2023

HDFS HDFS is the abbreviated form of Hadoop Distributed File System and is a component of Apache Hadoop. Before we understand what HDFS is, we first need to know what a file system is. HDFS is a technology that helps to store data in bigger chunks. HDFS is a technology that helps to store data in bigger chunks.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Cloudera

DECEMBER 8, 2021

One core component of CDP Operational Database, Apache HBase has been in the Hadoop ecosystem since 2008 and was optimised to run on HDFS. Feedback from customers is that they love the idea of using HBase on S3 but want the performance of HBase when deployed on HDFS. COD using m5.2xlarge instances and HBase using EBS (st1) based HDFS.

Database 89

Database AWS Datasets Cloud Storage 89

LinkedIn Engineering

JULY 19, 2023

Open source data lakehouse deployments are built on the foundations of compute engines (like Apache Spark, Trino, Apache Flink), distributed storage (HDFS, cloud blob stores), and metadata catalogs / table formats (like Apache Iceberg, Delta, Hudi, Apache Hive Metastore).

Big Data 78

Big Data Data Management Management Metadata 78

Christophe Blefari

SEPTEMBER 28, 2023

The era of Big Data was characterised by Hadoop, HDFS, distributed computing (Spark), above the JVM. We jumped from HDFS to Cloud Storage (S3, GCS) for storage and from Hadoop, Spark to Cloud warehouses (Redshift, BigQuery, Snowflake) for processing. This era was necessary and opened doors to the future, fostering innovation.

Cloud Storage 147

Cloud Storage Big Data Hadoop SQL 147

Knowledge Hut

APRIL 25, 2024

Hadoop provides a file system (HDFS) that is designed for scalability and reliability, as well as a resource manager (YARN) that enables efficient scheduling of job execution. HDFS, Cassandra, Hive). Here is a brief overview of some of the most popular big data technologies : Let's check what Hadoop big data technology is.

Big Data 98

Big Data Technology NoSQL Hadoop 98

Start Data Engineering

JUNE 26, 2020

EMR AWS EMR is a managed service provided by AWS to run Spark, HDFS, HIVE and other select software.

AWS 130

AWS Project Management 130

Cloudera

NOVEMBER 10, 2021

In CDH, Apache Sentry provided a stand-alone authorization module for Hadoop SQL components like Apache Hive and Apache Impala as well as other services like Apache Solr, Apache Kafka, and HDFS (limited to Hive table data). HDFS Access Sync implementation – Sentry Vs Ranger. Since CDP Private Cloud Base 7.1.5,

Hadoop 75

Hadoop SQL Database Kafka 75

U-Next

MARCH 1, 2023

It serves as HDFS’ main hub and keeps track of different files across groups and maintains HDFS data. What is HDFS’s whole name? What is HDFS’s whole name? Hadoop Distributed File System is known as HDFS. Explain HDFS’s Block and Block Scanner. DataNodes are used to keep the data.

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Cloudera

JULY 15, 2021

These include the HDFS NameNode, YARN ResourceManager, Impala Catalog/Statestore, HBase Master Server, and Kudu Masters. There should be a minimum of three master nodes, two of which will be HDFS Namenodes and YARN Resource Managers. In clusters of more than 200 nodes, five master nodes may be appropriate. Edge or Gateway.

Architecture 97

Architecture Cloud Kafka Hadoop 97

Cloudera

AUGUST 7, 2023

Introduction The snapshots feature of the Apache Hadoop Distributed Filesystem ( HDFS) enables you to capture point-in-time copies of the file system and protect your important data against corruption, user-, or application errors. For more information about using HDFS Snapshots, please read the Cloudera Documentation on the subject.

Hadoop 79

Hadoop Accessible Accessibility Professional Services 79

Cloudera

AUGUST 10, 2021

Prior to that, entities created with an Ozone path resulted in creating HDFS path entities. hdfs dfs -ls ofs://tpc.data.ozone1/. If you’re bringing your own, it’s as simple as creating the bucket in Ozone using the Hadoop CLI and putting the data you want there: hdfs dfs -mkdir ofs://ozone1/data/tpc/test. Using the Hadoop CLI.

Hadoop 103

Hadoop Kafka Datasets Government 103

LinkedIn Engineering

APRIL 4, 2023

The data needed to compute our metrics came from various sources including MySQL databases, Kafka topics and Hadoop (HDFS). We chose HDFS as our source data staging area because most of the other data sources at LinkedIn have a way to be exported into HDFS giving us a single access layer to all required data.

MySQL 122

MySQL Datasets Software Engineer Software Engineering 122

Cloudera

AUGUST 10, 2021

Further improvements in Ranger include the addition of audit events for HDFS superusers and a way of defining audit filters to reduce the amount of potential noise in the audit logs. The default filters exclude certain internal operations by the hdfs user and also the “getfileinfo” event.

Cloud 97

Cloud Kafka Metadata SQL 97

Cloudera

NOVEMBER 15, 2022

While it is possible to emulate a hierarchical file system view over object stores, the semantics compared to HDFS are very different. This was a non-issue on HDFS because HDFS provided atomic renames. Overcoming these caveats must be addressed by the accessing layer of the software architecture (HBase, in this case).

Database 76

Database Cloud Cloud Storage Architecture 76

Cloudera

OCTOBER 15, 2021

Below is a high-level view of Apache data analytics and the interactions between the storage systems like Apache HDFS, Apache Ozone, S3-like object stores, etc. We ran Apache Hadoop Teragen benchmark tests in a conventional Hadoop stack consisting of YARN and HDFS side by side with Apache Ozone.

Cloud 87

Cloud Hadoop Data Analytics Metadata 87

Cloudera

SEPTEMBER 28, 2020

Support Kafka connectivity to HDFS, AWS S3 and Kafka Streams. Sentry Hive / HDFS ACL sync is not included in CDP-DC 7.1 (on Transition from Navigator by migrating the business metadata (tags, entity names, custom properties, descriptions and technical metadata (Hive, Spark, HDFS, Impala) to Atlas. on roadmap).

Cloud 130

Cloud Kafka Professional Services Metadata 130

ProjectPro

JANUARY 31, 2023

Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. HBase storage is ideal for random read/write operations, whereas HDFS is designed for sequential processes. FSCK stands for File System Check, used by HDFS. HDFS indexes data blocks according to their size.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Cloudera

JUNE 25, 2021

Replication Manager can be used to migrate Apache Hive, Apache Impala, and HDFS objects from CDH clusters to CDP Public Cloud clusters. The Apache Ranger access policy model consists of two major components: Specification of the resources a policy is applied to, such as HDFS files and directories, Hive databases.

Cloud 68

Cloud Data Lake Cloud Storage Metadata 68

Cloudera

JANUARY 20, 2021

to make a classification model based off of training data stored in both Cloudera’s Operational Database (powered by Apache HBase) and Apache HDFS. Training Data in HBase and HDFS. In this demo, half of this training data is stored in HDFS and the other half is stored in an HBase table.

Machine Learning 111

Machine Learning Database Data Science Building 111

LinkedIn Engineering

MARCH 23, 2023

However, for batch processing, input data comes from bounded data sources, like HDFS. one side is Kafka, the other side is HDFS). Output is written to one or more databases.) In streaming processing, input data is always from unbounded data sources, like Kafka. This is prone to toil and error.

Process 97

Process Lambda Architecture Kafka Datasets 97

Cloudera

MARCH 5, 2024

Rolling upgrades are now supported for HDFS, Hive, HBase, Kudu, Kafka, Ranger, YARN, and Ranger KMS. Zero Downtime Upgrades Beyond improvements to Iceberg and Ozone, the platform now boasts Zero Downtime Upgrades (ZDU). ZDU gives organizations a more convenient means of upgrading.

Data Lake 87

Data Lake Government Data Storage Kafka 87

Uber Engineering

APRIL 5, 2018

Three years ago, Uber Engineering adopted Hadoop as the storage ( HDFS ) and compute ( YARN ) infrastructure for our organization’s big data analysis.

Hadoop 109

Hadoop Systems Big Data Data Analysis 109

Knowledge Hut

DECEMBER 28, 2023

Designing a Hadoop Architecture The process of designing a Hadoop project architecture system entails the integration of multiple components, including Hadoop Distributed File System ( HDFS ), Yet Another Resource Negotiator (YARN), and MapReduce. Able to write code effectively in languages like Java, Python, Scala, etc.

Hadoop 52

Hadoop Project Datasets Big Data 52

Cloudera

SEPTEMBER 1, 2020

More specifically: HDFS. Files that support Solr, such as Lucene index files and write-ahead logs, are also stored in HDFS. Using HDFS provides simpler provisioning on a larger base, redundancy, and fault tolerance. With HDFS, Solr servers are essentially stateless, so host failures have minimal consequences.

Cloud Storage 66

Cloud Storage Unstructured Data AWS Analytics Application 66

Cloudera

JUNE 15, 2021

Which security features we wish to enable – Kerberos, TLS, HDFS Transparent Data Encryption , LDAP integration, etc. There is a basic definition file provided in the cloudera-deploy repository; however this only includes the HDFS, YARN, and Zookeeper services. definition.yml – this holds our cluster definition content.

Cloud 82

Cloud AWS Kafka Management 82

Cloudera

JANUARY 26, 2021

Use Case 1: NiFi pulling data from Kafka and pushing it to a file system (like HDFS). With the flow running in HDF, you can set up the same flow in the CFM cluster, making sure to use the same “Group ID” in each ConsumeKafka processor configuration. . a load balancer is always set up in front of NiFi.

Kafka 76

Kafka Hadoop Data Ingestion Utilities 76

Jesse Anderson

DECEMBER 12, 2022

With an immutable file system like HDFS, we needed scalable databases to read and write data randomly. Hadoop was hard to program, and Apache Hive came along in 2010 to add SQL. Apache Pig in 2008 came too, but it didn’t ever see as much adoption. Apache HBase came in 2007, and Apache Cassandra came in 2008.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Cloudera

AUGUST 3, 2022

As a user, you need to specify two key configurations in the spark job: The staging directory: spark.datasource.hive.warehouse.load.staging.dir=hdfs://…/tmp/staging/hwc. Setup data staging area within HDFS and grant the required policies within Ranger to allow the user to perform: read, write, and execute on the staging path.

Datasets 85

Datasets BI Machine Learning Accessible 85

LinkedIn Engineering

JUNE 26, 2023

Current Gaps in Self-Service Depending on the systems involved, developers can often use Nuage, Azkaban, or a command-line tool to create a single "hop" from one system to another: Sources Destinations Kafka Brooklin Espresso MySQL HDFS Venice Kafka Huage N/A Azkaban Brooklin N/A N/A Nuage Nuage Espresso N/A MySQL N/A HDFS auto Nuage Nuage N/A Nuage (..)

Data Pipeline 112

Data Pipeline Kafka MySQL SQL 112

Christophe Blefari

JANUARY 20, 2024

It's important to understand the distributed computing concepts, MapReduce , Hadoop distributions , data locality , HDFS. A quick overview of what everyone used for years (and still using it for some of us). Data & Data Engineering — the past, present, and future ; this is a good overlook on data engineering history.

130

130

Cloudera

DECEMBER 18, 2020

However, if the block is not currently local to the Region Server process then that is counted as a cache miss and it must be read from the HFile in HDFS storage. Depending on cache utilization that block will then be saved in the cache for future requests. . You can find this info from the L1 cache hit ratio “ l1CacheHitRatio” config.

Datasets 58

Datasets NoSQL Accessible Accessibility 58

ProjectPro

FEBRUARY 18, 2022

Load the dataset into HDFS storage after downloading it. Using Spark, read data from HDFS storage and write it to an HBase database. Source Code- Retail Analytics using Sqoop, HDFS, and Hive Real-Time AWS Log Analytics You will create an end-to-end log analytics solution to gather, ingest, and process data in this project.

Project 52

Project AWS Kafka Healthcare 52

Data Engineering Podcast

SEPTEMBER 22, 2019

HDFS, GlusterFS, Ceph) What are some of the challenges that you face in terms of maintaining compatibility with the S3 interface? HDFS, GlusterFS, Ceph) What are some of the challenges that you face in terms of maintaining compatibility with the S3 interface? Your marketing focuses on the utility of MinIO for ML and AI workloads.

AWS 100

AWS Google Cloud Cloud Storage Data Lake 100