Designed by Sanjay Ghemawat , Howard Gobioff and Shun-Tak Leung of Google in 2002-03.
Provides fault tolerance, serving large number of clients with high aggregate performance.
The field of Google is beyond the searching.
Google store the data in more than 15 thousands commodity hardware.
Handles the exceptions of Google and other Google specific challenges in their distributed file system.
The Google File System (GFS) presented in 2003 is the inspiration for the Hadoop Distributed File System (HDFS). Let's take a deep dive into GFS to better understand Hadoop.
Designed by Sanjay Ghemawat , Howard Gobioff and Shun-Tak Leung of Google in 2002-03.
Provides fault tolerance, serving large number of clients with high aggregate performance.
The field of Google is beyond the searching.
Google store the data in more than 15 thousands commodity hardware.
Handles the exceptions of Google and other Google specific challenges in their distributed file system.
The Google File System (GFS) presented in 2003 is the inspiration for the Hadoop Distributed File System (HDFS). Let's take a deep dive into GFS to better understand Hadoop.
Google has designed and implemented a scalable distributed file system for their large distributed data intensive applications. They named it Google File System, GFS.
This Presentation is about NoSQL which means Not Only SQL. This presentation covers the aspects of using NoSQL for Big Data and the differences from RDBMS.
In recent years, we have seen an overwhelming number of TV commercials that promise that the Cloud can help with many problems, including some family issues. What stands behind the terms “Cloud” and “Cloud Computing,” and what we can actually expect from this phenomenon? A group of students of the Computer Systems Technology department and Dr. T. Malyuta, whom has been working with the Cloud technologies since its early days, will provide an overview of the business and technological aspects of the Cloud.
Building Reliable Lakehouses with Apache Flink and Delta LakeFlink Forward
Flink Forward San Francisco 2022.
Apache Flink and Delta Lake together allow you to build the foundation for your data lakehouses by ensuring the reliability of your concurrent streams from processing to the underlying cloud object-store. Together, the Flink/Delta Connector enables you to store data in Delta tables such that you harness Delta’s reliability by providing ACID transactions and scalability while maintaining Flink’s end-to-end exactly-once processing. This ensures that the data from Flink is written to Delta Tables in an idempotent manner such that even if the Flink pipeline is restarted from its checkpoint information, the pipeline will guarantee no data is lost or duplicated thus preserving the exactly-once semantics of Flink.
by
Scott Sandre & Denny Lee
Performance Troubleshooting Using Apache Spark MetricsDatabricks
Performance troubleshooting of distributed data processing systems is a complex task. Apache Spark comes to rescue with a large set of metrics and instrumentation that you can use to understand and improve the performance of your Spark-based applications. You will learn about the available metric-based instrumentation in Apache Spark: executor task metrics and the Dropwizard-based metrics system. The talk will cover how Hadoop and Spark service at CERN is using Apache Spark metrics for troubleshooting performance and measuring production workloads. Notably, the talk will cover how to deploy a performance dashboard for Spark workloads and will cover the use of sparkMeasure, a tool based on the Spark Listener interface. The speaker will discuss the lessons learned so far and what improvements you can expect in this area in Apache Spark 3.0.
Google has designed and implemented a scalable distributed file system for their large distributed data intensive applications. They named it Google File System, GFS.
This Presentation is about NoSQL which means Not Only SQL. This presentation covers the aspects of using NoSQL for Big Data and the differences from RDBMS.
In recent years, we have seen an overwhelming number of TV commercials that promise that the Cloud can help with many problems, including some family issues. What stands behind the terms “Cloud” and “Cloud Computing,” and what we can actually expect from this phenomenon? A group of students of the Computer Systems Technology department and Dr. T. Malyuta, whom has been working with the Cloud technologies since its early days, will provide an overview of the business and technological aspects of the Cloud.
Building Reliable Lakehouses with Apache Flink and Delta LakeFlink Forward
Flink Forward San Francisco 2022.
Apache Flink and Delta Lake together allow you to build the foundation for your data lakehouses by ensuring the reliability of your concurrent streams from processing to the underlying cloud object-store. Together, the Flink/Delta Connector enables you to store data in Delta tables such that you harness Delta’s reliability by providing ACID transactions and scalability while maintaining Flink’s end-to-end exactly-once processing. This ensures that the data from Flink is written to Delta Tables in an idempotent manner such that even if the Flink pipeline is restarted from its checkpoint information, the pipeline will guarantee no data is lost or duplicated thus preserving the exactly-once semantics of Flink.
by
Scott Sandre & Denny Lee
Performance Troubleshooting Using Apache Spark MetricsDatabricks
Performance troubleshooting of distributed data processing systems is a complex task. Apache Spark comes to rescue with a large set of metrics and instrumentation that you can use to understand and improve the performance of your Spark-based applications. You will learn about the available metric-based instrumentation in Apache Spark: executor task metrics and the Dropwizard-based metrics system. The talk will cover how Hadoop and Spark service at CERN is using Apache Spark metrics for troubleshooting performance and measuring production workloads. Notably, the talk will cover how to deploy a performance dashboard for Spark workloads and will cover the use of sparkMeasure, a tool based on the Spark Listener interface. The speaker will discuss the lessons learned so far and what improvements you can expect in this area in Apache Spark 3.0.
Second phase report on "ANALYZING THE EFFECTIVENESS OF THE ADVANCED ENCRYPTIO...Nikhil Jain
To implement and improve the performance of Advanced Encryption Standard algorithm by using multicore systems and Open MP API extracting as much parallelism as possible from the algorithm in parallel implementation approach.
I promise that understand NoSQL is as easy as playing with LEGO bricks ! The Google Bigtable presented in 2006 is the inspiration for Apache HBase: let's take a deep dive into Bigtable to better understand Hbase.
Cómo se diseña una base de datos que pueda ingerir más de cuatro millones de ...javier ramirez
En esta sesión voy a contar las decisiones técnicas que tomamos al desarrollar QuestDB, una base de datos Open Source para series temporales compatible con Postgres, y cómo conseguimos escribir más de cuatro millones de filas por segundo sin bloquear o enlentecer las consultas.
Hablaré de cosas como (zero) Garbage Collection, vectorización de instrucciones usando SIMD, reescribir en lugar de reutilizar para arañar microsegundos, aprovecharse de los avances en procesadores, discos duros y sistemas operativos, como por ejemplo el soporte de io_uring, o del balance entre experiencia de usuario y rendimiento cuando se plantean nuevas funcionalidades.
Introduction to OS LEVEL Virtualization & ContainersVaibhav Sharma
This Presentation contains information about os level virtualization and Containers internals. It has used other material on slide share which is referenced in Notes of PPT
The Proper Care and Feeding of MySQL DatabasesDave Stokes
Many Linux System Administrators are 'also' accidental database administrators. This is a guide for them to keep their MySQL database instances happy, health, and glowing
저사양 IoT 디바이스에 보안 기술 적용의 어려움을 해결하기 위해 oneM2M에서는 하드웨어 보안 모듈의 필요성을 제시하였다. 그러나 하드웨어 보안 모듈이 단독 동작하며, IoT 디바이스의 마이크로프로세서와 구분된 시스템은 또다른 보안 취약점이 될 수 있다. 본 논문에서는 통합 보안 SoC 기반의 IoT 디바이스 보안 플랫폼을 설계하여 oneM2M의 보안 요구 사항을 만족하는 요소 기술을 제안한다. 그리고 이를 통해 IoT 디바이스에 대한 보안 위협 대응을 검증한다.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Online aptitude test management system project report.pdfKamal Acharya
The purpose of on-line aptitude test system is to take online test in an efficient manner and no time wasting for checking the paper. The main objective of on-line aptitude test system is to efficiently evaluate the candidate thoroughly through a fully automated system that not only saves lot of time but also gives fast results. For students they give papers according to their convenience and time and there is no need of using extra thing like paper, pen etc. This can be used in educational institutions as well as in corporate world. Can be used anywhere any time as it is a web based application (user Location doesn’t matter). No restriction that examiner has to be present when the candidate takes the test.
Every time when lecturers/professors need to conduct examinations they have to sit down think about the questions and then create a whole new set of questions for each and every exam. In some cases the professor may want to give an open book online exam that is the student can take the exam any time anywhere, but the student might have to answer the questions in a limited time period. The professor may want to change the sequence of questions for every student. The problem that a student has is whenever a date for the exam is declared the student has to take it and there is no way he can take it at some other time. This project will create an interface for the examiner to create and store questions in a repository. It will also create an interface for the student to take examinations at his convenience and the questions and/or exams may be timed. Thereby creating an application which can be used by examiners and examinee’s simultaneously.
Examination System is very useful for Teachers/Professors. As in the teaching profession, you are responsible for writing question papers. In the conventional method, you write the question paper on paper, keep question papers separate from answers and all this information you have to keep in a locker to avoid unauthorized access. Using the Examination System you can create a question paper and everything will be written to a single exam file in encrypted format. You can set the General and Administrator password to avoid unauthorized access to your question paper. Every time you start the examination, the program shuffles all the questions and selects them randomly from the database, which reduces the chances of memorizing the questions.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
AKS UNIVERSITY Satna Final Year Project By OM Hardaha.pdf
Google File System
1. GOOGLE
FILE
SYSTEM
Presented by
Junyoung Jung (2012104030)
Jaehong Jeong (2011104050)
Dept. of Computer Engineering
Kyung Hee Univ.
Big Data Programming (Prof. Lee Hae Joon), 2017-Fall
4. 1.1 THIS PAPER…
4
The Google File System
- Sanjay Ghemeawat, Howard Gobioff, and Shun-Tak Leung
- Google
- 19th ACM Symposium on Operating System Principles, 2003
6. Previous Distributed File System
1.2 BACKGROUND
6
Performance Scalability Reliability Availabililty
GFS(Google File System) has the same goal.
However, it reflects a marked departure from some earlier file system.
7. 1. Component failures are the norm rather than the exception.
2. Files are huge by traditional standards.
3. Most files are mutated by appending new data.
4. Co-design applications and file system API.
5. Sustained bandwidth more critical than low latency.
1.3 DIFFERENT POINTS IN THE DESIGN SPACE
7
9. Familiar Interface
- create
- delete
- open
- close
- read
- write
2.1 INTERFACE
9
Moreover…
- Snapshot
ㆍ Low cost
ㆍ Make a copy of a file/directory tree
ㆍ Duplicate metadata
- Atomic Record append
ㆍ Atomicity with multiple concurrent writes
11. 2.2 ARCHITECTURE
11
Chunk
- Files are divided into fixed-size chunk
- 64MB
- Larger than typical file system block sizes
Advantages from large chunk size
- Reduce interaction between client and master
- Client can perform many operations on a given chunk
- Reduce size of metadata stored on the master
23. 3.1 LEASES & MUTATION ORDER
23
Objective
- Ensure data consistent & defined.
- Minimize load on master.
Master grants ‘lease’ to one replica
- Called ‘primary’ chunkserver.
Primary defines a mutation order between mutations
- All secondaries follows this order
25. 3.3 ATOMIC APPENDS
25
The Client Specifies only the data
Similar to writes
- Mutation order is determined by the primary
- All secondaries use the same mutation order
GFS appends data to the file at least once atomically
26. 3.4 SNAPSHOT
26
Goals
- To quickly create branch copies of huge data sets
- To easily checkpoint the current state
Copy-on-write technique
- Metadata for the source file or directory tree is duplicated.
- Reference count for chunks are incremented.
- Chunks are copied later at the first write.
27. MASTER OPERATION
Namespace Management and Locking
Replica Placement
Creation, Re-replication, Rebalancing
Garbage Collection
Stale Replica Detection 27
4
28. “ The master executes all
namespace operations and
manages chunk replicas
throughout the system.
2828
29. 4.1 Namespace Management and Locking
▰ Namespaces are represented as a lookup table mapping full
pathnames to metadata
▰ Use locks over regions of the namespace to ensure proper
serialization
▰ Each master operation acquires a set of locks before it runs
29
30. 4.1 Namespace Management and Locking
▰ Example of Locking Mechanism
▻ Preventing /home/user/foo from being created while /home/user is being snapshotted to /save/user
▻ Snapshot operation
▻ - Read locks on /home and /save
▻ - Write locks on /home/user and /save/user
▻ File creation
▻ - Read locks on /home and /home/user
▻ - Write locks on /home/user/foo
▻ Conflict locks on /home/user
▰ Locking scheme is that it allows concurrent mutations in
the same directory
30
31. 4.2 Replica Placement
▰ The chunk replica placement policy serves two purposes:
▻ Maximize data reliability and availability
▻ Maximize network bandwidth utilization.
31
32. 4.3 Creation, Re-replication, Rebalancing
▰ Creation
▻ Disk space utilization
▻ Number of recent creations on each chunkserver
▰ Re-replication
▻ Prioritized: How far it is from its replication goal…
▻ The highest priority chunk is cloned first by copying the chunk data directly from an existing replica
▰ Rebalancing
▻ Periodically
32
33. 4.4 Garbage Collection
▰ Deleted files
▻ Deletion operation is logged
▻ File is renamed to a hidden name, then may be removed later or get recovered
▰ Orphaned chunks (unreachable chunks)
▻ Identified and removed during a regular scan of the chunk namespace
33
34. 4.5 Stale Replica Detection
▰ Stale replicas
▻ Chunk version numbering
▻ The client or the chunkserver verifies the version number when it performs the
operation so that it is always accessing up-to-date data.
34
35. FAULT TOLERANCE AND DIAGNOSIS
High Availability
Data Integrity
Diagnostic Tools
35
5
36. “ We cannot completely trust the
machines, nor can we completely
trust the disks.
3636
37. 5.1 High Availability
▰ Fast Recovery
▻ - Operation log and Checkpointing
▰ Chunk Replication
▻ - Each chunk is replicated on multiple chunkservers on different racks
▰ Master Replication
▻ - Operation log and check points are replicated on multiple machines
37
38. 5.2 Data Integrity
▰ Checksumming to detect corruption of stored data
▰ Each chunkserver independently verifies the integrity
38
39. 5.3 Diagnostic Tools
▰ Extensive and detailed diagnostic logging has helped
immeasurably in problem isolation, debugging, and
performance analysis, while incurring only a minimal cost .
▰ RPC requests and replies, etc..
39
41. “ A few micro-benchmarks to
illustrate the bottlenecks
inherent in the GFS architecture
and implementation
4141
42. 6.1 Micro-benchmarks
▰ One master, two master replicas, 16 chunkservers, and 16
clients. (2003)
▰ All the machines are configured with dual 1.4 GHz PIII
processors, 2 GB of memory, two 80 GB 5400 rpm disks,
and a 100 Mbps full-duplex Ethernet connection to an HP
2524 switch.
42