Protocol buffers
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Protocol buffers are a flexible, efficient, and automated mechanism for serializing structured data that is simpler, faster, smaller and generates access classes compared to XML and JSON. It works by defining message types in .proto files that can then be compiled to generate data access classes in various languages like Java, C++, Python and more. Many large companies like Google, Twitter and Oracle use protocol buffers for internal APIs, queue systems and database objects due to its performance advantages over other data formats.
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PHP vs Python Which is Best for Web Development.pdf
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More from Manuel Correa
How Netflix does Microservices
This document discusses how Netflix implements microservices. It outlines key principles such as modeling services around business domains, decentralizing all things, designing for failure, and making systems highly observable. Services are autonomous and communicate through dumb pipes and smart endpoints. Netflix uses service discovery, dynamic configuration, circuit breakers, and chaos testing to make services resilient and prevent failures from cascading. The document emphasizes that each service needs a fallback strategy and that a reliable routing layer is essential for microservices architectures to function properly at Netflix's scale.
Ads final project
This document summarizes an implementation of Apache Lucene and Solr to build a distributed search engine across large datasets. It implemented Hadoop HDFS for distributed storage, integrated Solr instances for indexing and searching over 500 columns of data from government databases totaling over 200,000 documents and 15 million data items. A Solr client web application was also developed to demonstrate the distributed search capabilities over the indexed data.
Big table
BigTable is a distributed storage system designed by Google to manage large amounts of structured data across thousands of machines. It is a sparse, multidimensional sorted map that scales to petabytes of data. BigTable uses other Google technologies like Google File System for storage, and MapReduce for distributed computations. Data is stored across tablets that are dynamically partitioned and distributed among tablet servers for high performance and availability.
Big table
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Optimal Adaptation
1) The document presents frameworks for optimal adaptation in autonomic web processes that have inter-service dependencies. It describes two approaches: M-MDP which uses a centralized Markov decision process and MDP-COM which uses a decentralized approach with local Markov decision processes and a coordination mechanism.
2) The supply chain example involves ordering computer parts from suppliers, with the goal of minimizing costs and response times while maintaining compatibility between parts. External events like delivery delays require adaptation.
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Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
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Overview
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This video focuses on integration of Salesforce with Bonterra Impact Management.
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Protocol buffers
- 2. What are protocol buffers? ● Flexible, efficient, and automated mechanism for Serializing data ● Over XML and JSON, Proto-Buffer is o Binary o Simpler o Faster o Smaller (space) o Generates access classes as part of the framework
- 3. How does it work? .proto file
- 4. What languages translate to? ● Java, C++, C, Ruby, Python, C#, Clojure, Lisp, Dart, Erlang, Go, Android, Javascript, Matlab, Perl, Objective C, PHP, Scala, VB, Julia, Lua, and … ● Applications o Internal APIs o Queue systems o Database Objects
- 5. Quick dirty Space performance
- 6. Who is using it? source: documentation, slideshare, etc.. ● Google ● Twitter ● Oracle ● ...
- 7. Reference ● Google Developer Guide ● JavaOne presentation: RESTFul Protocol buffers ● Hadoop and Protocol Buffers at Twitter