Manging scalability of distributed system

This document provides an overview of PNUTS, Yahoo!'s hosted data serving platform. The key points are: 1. PNUTS is a massively parallel and geographically distributed database system that provides a consistency model between full serializability and eventual consistency, through per-record timeline consistency. 2. It uses asynchronous geographic replication to replicas around the world for high availability and low latency updates. Notifications allow subscribers to stream updates. Bulk loading facilitates rapid data ingestion. 3. The architecture involves record-level mastering, storage units, tablet controllers, routers, and a message broker to propagate updates between regions while ensuring consistency.

The document discusses scheduling in the Linux, Windows, and Solaris operating systems. In Linux, tasks are divided into scheduling classes and the scheduler selects the highest priority task in the highest priority class to run. The two main classes are the default class which uses Completely Fair Scheduler, and the real-time class. Windows uses a priority-based preemptive scheduler where the highest priority ready thread runs, and a higher priority thread can preempt a lower one. Solaris has six priority-based classes and uses different scheduling algorithms depending on the class, like time-sharing with dynamic time slices or real-time with static highest priority.

This document discusses NoSQL and big data processing. It provides background on scaling relational databases and introduces key concepts like the CAP theorem. The CAP theorem states that a distributed data store can only provide two out of three guarantees around consistency, availability, and partition tolerance. Many NoSQL systems sacrifice consistency for availability and partition tolerance, adopting an eventual consistency model instead of ACID transactions.

This document discusses session management challenges for web applications in elastic infrastructure as a service (IaaS) systems. It presents two architectural solutions - session monitoring and session migration - to support scaling down operations while maintaining sticky sessions. The authors implemented session monitoring in the open source Eucalyptus IaaS system by adding a load balancer, monitor, and control daemon to track sessions and safely remove servers from the cluster. Future work includes evaluating the prototype's performance.

1. There are two main approaches to distributed mutual exclusion - token-based and non-token based. Token based approaches use a shared token to allow only one process access at a time, while non-token approaches use message passing to determine access order. 2. A common token based algorithm uses a centralized coordinator process that grants access to the requesting process. Ring-based algorithms pass a token around a logical ring, allowing the process holding it to enter the critical section. 3. Lamport's non-token algorithm uses message passing of requests and timestamps to build identical request queues at each process, allowing the process at the head of the queue to enter the critical section. The Ricart-Agrawala

- A distributed system is a collection of autonomous computers linked by a network that appear as a single computer. Inter-process communication allows processes running on different computers to exchange data. Common IPC methods include message passing, shared memory, and remote procedure calls. - Marshalling is the process of reformatting data to allow exchange between modules that use different data representations. Remote procedure calls allow a program to execute subroutines in another address space, such as on another computer. The client-server model partitions tasks between service providers (servers) and requesters (clients). - Election algorithms are used in distributed systems to choose a coordinator process from among a group of processes. Examples include the bully algorithm and ring

The document outlines the key performance testing requirements when using LoadRunner. It discusses factors that impact throughput like hardware specifications, software processing overhead, and degree of parallelism. It also defines different types of performance tests including load testing to determine maximum load, stress testing under deprived resources, soak testing under prolonged load, and scalability testing to determine if an application can scale. Finally, it lists requirements for scripts, parametrization, correlations, scenarios, think times, and monitoring tools for capacity planning when using LoadRunner for performance testing.

This is the Complete Information about Data Replication you need, i am focused on these topics: What is replication? Who use it? Types ? Implementation Methods?

StrikrSystemsLLP provides automation services to help identify automation requirements, plan proof of concepts and development work, and drive efficiency. They take a modular approach to design reusable automation solutions across organizations. Their process involves understanding existing systems and scripts, exploring automation opportunities, and designing data-driven solutions without resume-driven frameworks or outdated tools like Excel. They deliver integrated services and aim to eliminate user interaction from automated processes.

This lecture covers process and thread concepts in operating systems including scheduling criteria and algorithms. It discusses key process concepts like process state, process control block and CPU scheduling. Common scheduling algorithms like FCFS, SJF, priority and round robin are explained. Process scheduling queues and the producer-consumer problem are also summarized. Evaluation methods for scheduling algorithms like deterministic modeling, queueing models and simulation are briefly covered.

This presentation discusses database transactions. Key points: 1. A transaction must follow the properties of atomicity, consistency, isolation, and durability (ACID). It accesses and possibly updates data items while preserving a consistent database. 2. Transaction states include active, partially committed, failed, aborted, and committed. Atomicity and durability are implemented using a shadow database with a pointer to the current consistent copy. 3. Concurrent transactions are allowed for better throughput and response time. Concurrency control ensures transaction isolation to prevent inconsistent databases. 4. A schedule specifies the execution order of transaction instructions. A serializable schedule preserves consistency like a serial schedule. Conflict and view serializability are forms

This document discusses various topics related to communication and synchronization in distributed systems. It covers concepts like communication protocols, remote procedure calls, client-server and peer-to-peer models, blocking vs non-blocking communication, reliability, group communication, message ordering, and synchronization techniques including clock synchronization algorithms, mutual exclusion algorithms, and atomic transactions.

This document discusses transaction management and concurrency control. It defines a transaction as a logical unit of work that must be completed or aborted with no intermediate states. It describes the ACID properties of atomicity, consistency, isolation, and durability that transactions should have. It also discusses concurrency control techniques like locking and time stamping to ensure transactions execute serially for consistency despite concurrent access.

Event Ordering Mutual Exclusion Atomicity Concurrency Control Deadlock Handling Election Algorithms Reaching Agreement

Transactions and Concurrency Control in distributed systems. Transaction properties, classification, and transaction implementation. Flat, Nested, and Distributed transactions. Inconsistent Retrievals, Lost Update, Dirty Read, and Premature Writes Problem