How can you use PosgreSQL as a schemaless (NoSQL) database? Here we cover our use case and highlight upcoming features in postgres 9.4 and its integration with Django 1.7
1) MongoDB is used to collect analytics data from GitHub pages in real-time with over 10-15 million page views per day stored across 13 servers.
2) Data is stored in a denormalized manner across multiple collections to optimize for space, RAM, and read performance while live querying is supported.
3) As data volume grows over time, the data will need to be partitioned either by time frame, functionality, or individual servers to support the increased load.
The document discusses NoSQL databases and MongoDB in particular. It provides examples of MongoDB documents with different data types like objects, arrays, etc. It also shows how data is stored across multiple shard servers and accessed via mongos query routers. Configuration servers store sharded cluster metadata. Log data can be stored in MongoDB but only aggregated results data may be needed. HDFS is better for temporary raw log storage.
This summary provides an overview of Buddy Media's experience using MongoDB for three stages of a project:
Stage 1 was a non-critical logging application where they learned MongoDB is not like MySQL and to use subdocuments instead of rows/tables.
Stage 2 involved critical user data with spikes where they learned to use modifier operators carefully and implement indexing and replica sets.
Stage 3 was for real-time analytics of user events, requiring flexibility and high write volumes. They store aggregated metrics instead of individual events and use upserts and $inc to update in bulk, providing faster performance than SQL for their needs.
This document introduces MongoDB, a non-relational database that uses flexible, JSON-like documents with dynamic queries and indexing. MongoDB is horizontally scalable, supports replication and auto-sharding. It is suitable for caching, the web, and high-volume applications, but less suitable for highly transactional or offline business intelligence workloads. The document provides examples of basic CRUD operations and queries in MongoDB.
RethinkDB is an open-source, scalable JSON database built for real-time applications that allows data to be continuously pushed to clients in real-time instead of polling for changes like traditional databases. It supports installation on Ubuntu, OS X, CentOS and Debian and programmatic access through JavaScript, Ruby, and Python drivers. Queries can be run from the command line or through RethinkDB's own declarative query language called Reql. RethinkDB also supports features like indexing, aggregation, transactions, and multi-master replication across multiple machines.
This document provides an overview of MongoDB, including its key features such as document-oriented storage, full index support, replication and high availability, auto sharding, querying capabilities, and fast in-place updates. It also discusses MongoDB's architecture for replication, sharding, and configuration servers.
This document summarizes a presentation about RethinkDB, an open-source database built on JSON documents. It discusses key features of RethinkDB like supporting queries, being distributed, and ease of administration. It also compares RethinkDB to other NoSQL databases. The document provides examples of using the ReQL query language in Python to create and query a database. It demonstrates how to perform operations like counts, filters, and map-reduce queries.
1) MongoDB is used to collect analytics data from GitHub pages in real-time with over 10-15 million page views per day stored across 13 servers.
2) Data is stored in a denormalized manner across multiple collections to optimize for space, RAM, and read performance while live querying is supported.
3) As data volume grows over time, the data will need to be partitioned either by time frame, functionality, or individual servers to support the increased load.
The document discusses NoSQL databases and MongoDB in particular. It provides examples of MongoDB documents with different data types like objects, arrays, etc. It also shows how data is stored across multiple shard servers and accessed via mongos query routers. Configuration servers store sharded cluster metadata. Log data can be stored in MongoDB but only aggregated results data may be needed. HDFS is better for temporary raw log storage.
This summary provides an overview of Buddy Media's experience using MongoDB for three stages of a project:
Stage 1 was a non-critical logging application where they learned MongoDB is not like MySQL and to use subdocuments instead of rows/tables.
Stage 2 involved critical user data with spikes where they learned to use modifier operators carefully and implement indexing and replica sets.
Stage 3 was for real-time analytics of user events, requiring flexibility and high write volumes. They store aggregated metrics instead of individual events and use upserts and $inc to update in bulk, providing faster performance than SQL for their needs.
This document introduces MongoDB, a non-relational database that uses flexible, JSON-like documents with dynamic queries and indexing. MongoDB is horizontally scalable, supports replication and auto-sharding. It is suitable for caching, the web, and high-volume applications, but less suitable for highly transactional or offline business intelligence workloads. The document provides examples of basic CRUD operations and queries in MongoDB.
RethinkDB is an open-source, scalable JSON database built for real-time applications that allows data to be continuously pushed to clients in real-time instead of polling for changes like traditional databases. It supports installation on Ubuntu, OS X, CentOS and Debian and programmatic access through JavaScript, Ruby, and Python drivers. Queries can be run from the command line or through RethinkDB's own declarative query language called Reql. RethinkDB also supports features like indexing, aggregation, transactions, and multi-master replication across multiple machines.
This document provides an overview of MongoDB, including its key features such as document-oriented storage, full index support, replication and high availability, auto sharding, querying capabilities, and fast in-place updates. It also discusses MongoDB's architecture for replication, sharding, and configuration servers.
This document summarizes a presentation about RethinkDB, an open-source database built on JSON documents. It discusses key features of RethinkDB like supporting queries, being distributed, and ease of administration. It also compares RethinkDB to other NoSQL databases. The document provides examples of using the ReQL query language in Python to create and query a database. It demonstrates how to perform operations like counts, filters, and map-reduce queries.
Andrew Dunstan 9.3 JSON Presentation @ Postgres Open 2013PostgresOpen
This document discusses PostgreSQL's support for JSON, including:
- An overview of new features in versions 9.2 and 9.3 for JSON production, processing, and extraction.
- Explanations of JSON data types, operators, and functions added in 9.3 for converting between JSON and other PostgreSQL types.
- Examples of using the new JSON operators and functions to extract, transform, and produce JSON.
- Details on leveraging the new JSON C API to build custom JSON functions and transformations.
- Discussions of future work, like a possible binary JSON representation, to further improve PostgreSQL's JSON support.
MongoDB.local DC 2018: Ch-Ch-Ch-Ch-Changes: Taking Your MongoDB Stitch Applic...MongoDB
MongoDB Stitch is a serverless platform designed to help you easily and securely build an application on top of MongoDB Atlas. It lets developers focus on building applications rather than on managing data manipulation code, service integration, or backend infrastructure. MongoDB Stitch also makes it simple to respond to backend changes immediately, allowing you to simplify client side code and build complex flows more easily. This talk will cover ways that MongoDB Stitch helps you respond to changes in your database and take your applications to the next level.
Introduction to MongoDB
MongoDB Database
Document Model
BSON
Data Model
CRUD operations
High Availability and Scalability
Replication
Sharding
Hands-On MongoDB
The document discusses MongoDB, a non-relational database that uses documents with a flexible schema rather than tables, and is well-suited for applications that need to store data in complex, nested structures. It provides an overview of key MongoDB concepts like collections, queries, indexing, updating documents, and aggregation capabilities. Examples are given of how MongoDB can be used for applications involving user profiles, blogs, and logging.
This document provides an overview of querying and aggregation on MongoDB. It discusses querying concepts like find(), indexes, and $where queries. It also covers aggregation methods like count, sum, distinct, and group to perform more complex aggregation by grouping documents. Examples are given for common queries and aggregations including counting documents, finding population sums by state, and finding largest/smallest cities by state.
Back to Basics 2017: Mí primera aplicación MongoDBMongoDB
Descubra:
Cómo instalar MongoDB y usar el shell de MongoDB
Las operaciones básicas de CRUD
Cómo analizar el rendimiento de las consultas y añadir un índice
MongoDB is a document-oriented NoSQL database that uses a document-data model. It provides horizontal scaling with auto-sharding and replication. MongoDB can store documents in collections without a defined schema and support dynamic queries and indexing. RealNetworks uses MongoDB with Scala and other technologies for an Android app to send notifications to devices with installed RealNetworks applications at scale.
A presentation by Aicha Khabil (Responsable IT à l'université Alger 3) done during the 11th edition of Algiers Tech Meetup on October 8th 2016, at Djezzy Training Center (Algiers)
Ebook Pembuatan Aplikasi Rental film 2012yantoit2011
This document provides instructions for creating a film rental application program using Visual Basic. It includes requirements for installing Visual Basic 6.0, Crystal Reports 8.5, and additional components. It also provides an overview of the program's main form, properties to configure, and code listings for form controls and modules to connect to an Access database called dbssewafilm.
Back to Basics Spanish 4 Introduction to shardingMongoDB
Cómo MongoDB amplía el rendimiento de las operaciones de escritura y maneja grandes tamaño de datos
Cómo crear un sharded cluster básico
Cómo elegir una clave de sharding
For applications that outgrow the resources of a single database server, MongoDB can convert to a sharded cluster, automatically managing failover and balancing of nodes, with few or no changes to the original application code. This talk starts by discussing when to shard and continues on to describe MongoDB's sharding architecture. We'll describe how to configure a shard cluster and provide several example topologies. We'll also give some advice on schema design for sharding and how to pick the best shard key.
The document provides examples of updating documents in MongoDB. It demonstrates updating a username field, adding a new age field, and adding a new family subdocument to an existing document. Each update example finds the document, modifies the desired field(s), and uses update to overwrite the document with the changes.
Connecting and using PostgreSQL database with psycopg2 [Python 2.7]Dinesh Neupane
This presentation covers the basic idea of connecting postgresql database with python and psycopg2 module.
Covered Topics:
1. Psycopg2 Installation
2. Connecting to PostgreSQL Database
3. Connection Parameters
4. Create and Drop Table
5. Adaptation of Python Values to SQL Types
6. SQL Transactions
7. DML
MongoDB Days Silicon Valley: Winning the Dreamforce Hackathon with MongoDBMongoDB
Presented by Greg Deeds, CEO, Technology Exploration Group
Experience level: Introductory
A two person team using MongoDB and Salesforce.com created a geospatial machine learning tool from various datasets, parsing, indexing, and mapreduce in 24 hours. The amazing hack that beat 350 teams from around the world designer Greg Deeds will speak on getting to the winners circle with MongoDB power. It was MongoDB that proved to be the teams secret weapon to level the playing field for the win!
The document discusses MongoDB performance optimization strategies presented by Moshe Kaplan at a VP R&D Open Seminar. It covers topics like sharding, in-memory databases, MapReduce, profiling, indexes, server stats, schema design, and locking in MongoDB. Slides include information on tuning configuration parameters, analyzing profiling results, explain plans, index management, and database stats.
This document discusses MongoDB infrastructure at Server Density. It notes that Server Density uses 27 MongoDB nodes to store 20TB of data per month from their MySQL database. Some key reasons for choosing MongoDB include replication, official drivers, easy deployment, and fast performance out of the box. The document then discusses various MongoDB performance and infrastructure considerations like network throughput, replication lag, failover processes, disk types, backups, and monitoring.
Back to Basics Webinar 2: Your First MongoDB ApplicationMongoDB
The document provides instructions for installing and using MongoDB to build a simple blogging application. It demonstrates how to install MongoDB, connect to it using the mongo shell, insert and query sample data like users and blog posts, update documents to add comments, and more. The goal is to illustrate how to model and interact with data in MongoDB for a basic blogging use case.
For the first time in India, Technomed introduces "HEX-SERIES"Hexagonal led light provide Excellent cold light , without temperature rising. Special Features Like:- Memory Function, Endomode, Touch Controller, High quality sterilizable handle. we offer best quality product at cheapest price.....
The document discusses evaluating the validity and credibility of websites as sources for research. It identifies several factors to consider, including the web address extension (.com, .gov, etc.), author information, purpose (to persuade, inform or entertain), publication details like date and broken links, and currentness of information. Once a site is deemed valid, the document advises taking notes by paraphrasing rather than copying verbatim and focusing on essential facts. It stresses the importance of citing all sources used by gathering details like author, title, organization, date, URL and date accessed.
Andrew Dunstan 9.3 JSON Presentation @ Postgres Open 2013PostgresOpen
This document discusses PostgreSQL's support for JSON, including:
- An overview of new features in versions 9.2 and 9.3 for JSON production, processing, and extraction.
- Explanations of JSON data types, operators, and functions added in 9.3 for converting between JSON and other PostgreSQL types.
- Examples of using the new JSON operators and functions to extract, transform, and produce JSON.
- Details on leveraging the new JSON C API to build custom JSON functions and transformations.
- Discussions of future work, like a possible binary JSON representation, to further improve PostgreSQL's JSON support.
MongoDB.local DC 2018: Ch-Ch-Ch-Ch-Changes: Taking Your MongoDB Stitch Applic...MongoDB
MongoDB Stitch is a serverless platform designed to help you easily and securely build an application on top of MongoDB Atlas. It lets developers focus on building applications rather than on managing data manipulation code, service integration, or backend infrastructure. MongoDB Stitch also makes it simple to respond to backend changes immediately, allowing you to simplify client side code and build complex flows more easily. This talk will cover ways that MongoDB Stitch helps you respond to changes in your database and take your applications to the next level.
Introduction to MongoDB
MongoDB Database
Document Model
BSON
Data Model
CRUD operations
High Availability and Scalability
Replication
Sharding
Hands-On MongoDB
The document discusses MongoDB, a non-relational database that uses documents with a flexible schema rather than tables, and is well-suited for applications that need to store data in complex, nested structures. It provides an overview of key MongoDB concepts like collections, queries, indexing, updating documents, and aggregation capabilities. Examples are given of how MongoDB can be used for applications involving user profiles, blogs, and logging.
This document provides an overview of querying and aggregation on MongoDB. It discusses querying concepts like find(), indexes, and $where queries. It also covers aggregation methods like count, sum, distinct, and group to perform more complex aggregation by grouping documents. Examples are given for common queries and aggregations including counting documents, finding population sums by state, and finding largest/smallest cities by state.
Back to Basics 2017: Mí primera aplicación MongoDBMongoDB
Descubra:
Cómo instalar MongoDB y usar el shell de MongoDB
Las operaciones básicas de CRUD
Cómo analizar el rendimiento de las consultas y añadir un índice
MongoDB is a document-oriented NoSQL database that uses a document-data model. It provides horizontal scaling with auto-sharding and replication. MongoDB can store documents in collections without a defined schema and support dynamic queries and indexing. RealNetworks uses MongoDB with Scala and other technologies for an Android app to send notifications to devices with installed RealNetworks applications at scale.
A presentation by Aicha Khabil (Responsable IT à l'université Alger 3) done during the 11th edition of Algiers Tech Meetup on October 8th 2016, at Djezzy Training Center (Algiers)
Ebook Pembuatan Aplikasi Rental film 2012yantoit2011
This document provides instructions for creating a film rental application program using Visual Basic. It includes requirements for installing Visual Basic 6.0, Crystal Reports 8.5, and additional components. It also provides an overview of the program's main form, properties to configure, and code listings for form controls and modules to connect to an Access database called dbssewafilm.
Back to Basics Spanish 4 Introduction to shardingMongoDB
Cómo MongoDB amplía el rendimiento de las operaciones de escritura y maneja grandes tamaño de datos
Cómo crear un sharded cluster básico
Cómo elegir una clave de sharding
For applications that outgrow the resources of a single database server, MongoDB can convert to a sharded cluster, automatically managing failover and balancing of nodes, with few or no changes to the original application code. This talk starts by discussing when to shard and continues on to describe MongoDB's sharding architecture. We'll describe how to configure a shard cluster and provide several example topologies. We'll also give some advice on schema design for sharding and how to pick the best shard key.
The document provides examples of updating documents in MongoDB. It demonstrates updating a username field, adding a new age field, and adding a new family subdocument to an existing document. Each update example finds the document, modifies the desired field(s), and uses update to overwrite the document with the changes.
Connecting and using PostgreSQL database with psycopg2 [Python 2.7]Dinesh Neupane
This presentation covers the basic idea of connecting postgresql database with python and psycopg2 module.
Covered Topics:
1. Psycopg2 Installation
2. Connecting to PostgreSQL Database
3. Connection Parameters
4. Create and Drop Table
5. Adaptation of Python Values to SQL Types
6. SQL Transactions
7. DML
MongoDB Days Silicon Valley: Winning the Dreamforce Hackathon with MongoDBMongoDB
Presented by Greg Deeds, CEO, Technology Exploration Group
Experience level: Introductory
A two person team using MongoDB and Salesforce.com created a geospatial machine learning tool from various datasets, parsing, indexing, and mapreduce in 24 hours. The amazing hack that beat 350 teams from around the world designer Greg Deeds will speak on getting to the winners circle with MongoDB power. It was MongoDB that proved to be the teams secret weapon to level the playing field for the win!
The document discusses MongoDB performance optimization strategies presented by Moshe Kaplan at a VP R&D Open Seminar. It covers topics like sharding, in-memory databases, MapReduce, profiling, indexes, server stats, schema design, and locking in MongoDB. Slides include information on tuning configuration parameters, analyzing profiling results, explain plans, index management, and database stats.
This document discusses MongoDB infrastructure at Server Density. It notes that Server Density uses 27 MongoDB nodes to store 20TB of data per month from their MySQL database. Some key reasons for choosing MongoDB include replication, official drivers, easy deployment, and fast performance out of the box. The document then discusses various MongoDB performance and infrastructure considerations like network throughput, replication lag, failover processes, disk types, backups, and monitoring.
Back to Basics Webinar 2: Your First MongoDB ApplicationMongoDB
The document provides instructions for installing and using MongoDB to build a simple blogging application. It demonstrates how to install MongoDB, connect to it using the mongo shell, insert and query sample data like users and blog posts, update documents to add comments, and more. The goal is to illustrate how to model and interact with data in MongoDB for a basic blogging use case.
For the first time in India, Technomed introduces "HEX-SERIES"Hexagonal led light provide Excellent cold light , without temperature rising. Special Features Like:- Memory Function, Endomode, Touch Controller, High quality sterilizable handle. we offer best quality product at cheapest price.....
The document discusses evaluating the validity and credibility of websites as sources for research. It identifies several factors to consider, including the web address extension (.com, .gov, etc.), author information, purpose (to persuade, inform or entertain), publication details like date and broken links, and currentness of information. Once a site is deemed valid, the document advises taking notes by paraphrasing rather than copying verbatim and focusing on essential facts. It stresses the importance of citing all sources used by gathering details like author, title, organization, date, URL and date accessed.
Innovators Jumpstart 2015- McInnes Cooper (Business Structure Basics)PlanetHatch
This document provides an overview of key business structure and legal considerations for new businesses. It discusses reasons to incorporate, such as tax incentives and liability protection. It also summarizes important employment, tax, intellectual property, commercial leasing, insurance, and client considerations. Directors are liable for payroll tax remittances even after incorporation. Intellectual property can include patents, trademarks, copyrights, and data. Commercial leases require clarity to avoid additional rental costs or inventory seizure. Liability insurance is strongly recommended to protect the business. Waivers and disclaimers can provide additional legal protection.
Charmaine Cooper is the Community Engagement Coordinator for Wingecarribee Shire Council. Her role is to develop strong communication networks between the community and council and support public participation in council decision making. She facilitates engagement activities like surveys, meetings, and online forums to gather community input on projects and plans. The document outlines council's community engagement strategy, toolkit, and past engagement projects on issues like environmental plans and infrastructure projects. It provides guidance for councillors, staff and committees on their roles in engagement activities.
This document proposes a mobile app that allows users to locate public toilets around the world, rate them on cleanliness and other factors, and share reviews. The app would take advantage of Google Maps APIs and crowdsourced data to provide toilet locations and ratings. It aims to improve public toilet access and quality by giving users a way to find and provide feedback on facilities.
BLUECHIP TECHNOLOGY is working for the promotion of Engineering education and technology in India. We are the Professionals who are united together and working for the promotion of technology. To achieve our goal, we have made collaboration with a number of institutions and firms. BLUECHIP TECHNOLOGY provide open platform for the development of the various computer software. We are the part of Linux Promotion Organization.
The forums at BionicMe.com are allowing humanity to move forward through the study and discussion of bionics, robotics, prosthetics, artificial intelligence, nanotechnology and virtual reality.
Theo đó, các biệt thự loại A có diện tích đất từ 450 - 500 m2, diện tích sử dụng là 300 – 350 m2 được bố trí cho các Uỷ viên Bộ Chính trị, Ban Bí thư.
Biệt thự loại B với diện tích đất tối đa 350 - 400 m2, diện tích sử dụng từ 250 - 300 m2 được bố trí cho các chức danh có hệ số lương khởi điểm từ 10,4 trở lên (trừ chức danh Uỷ viên Bộ Chính trị, Ban Bí thư).
Nhà công vụ là căn hộ chung cư loại 1 tại khu vực đô thị, có diện tích sử dụng 140 – 160 m2, được bố trí cho các chức danh có hệ số lương khởi điểm từ 9,7 trở lên đến dưới 10,4.
Tương tự, căn hộ chung cư loại 2 có diện tích sử dụng từ 100 – 115 m2 được bố trí cho các chức danh có hệ số phụ cấp chức vụ từ 1,3 trở lên; Trung tướng, Thiếu tướng trong các lực lượng vũ trang; nhà khoa học được giao chủ trì nhiệm vụ khoa học và công nghệ cấp quốc gia đặc biệt quan trọng theo quy định của Luật Khoa học và Công nghệ và các chức danh tương đương.
Nhà công vụ là căn hộ chung cư loại 3 tại khu vực đô thị hoặc căn nhà loại 1 tại khu vực nông thôn có diện tích sử dụng từ 80 – 90 m2 được bố trí cho các chức danh có hệ số phụ cấp chức vụ từ 0,7 đến dưới 1,3; chuyên viên cao cấp (A3); giáo viên, bác sĩ và nhân viên y tế có chức danh tương đương đến công tác tại khu vực nông thôn xã vùng sâu, vùng xa, vùng có điều kiện kinh tế - xã hội đặc biệt khó khăn, khu vực biên giới, hải đảo; Đại tá, Thượng tá, Trung tá trong các lực lượng vũ trang; nhà khoa học được giao chủ trì nhiệm vụ khoa học và công nghệ cấp quốc gia đặc biệt quan trọng theo quy định của Luật Khoa học và Công nghệ và các chức danh tương đương.
Các căn hộ chung cư loại 4 tại khu vực đô thị có diện tích sử dụng 60 – 70 m2 hoặc căn nhà loại 2 tại khu vực nông thôn có diện tích sử dụng 55-65 m2 sẽ được bố trí cho các chức danh có hệ số phụ cấp chức vụ từ 0,2 đến dưới 0,7; chuyên viên chính (A2); giáo viên, bác sĩ và nhân viên y tế có chức danh tương đương đến công tác tại khu vực nông thôn xã vùng sâu, vùng xa, vùng có điều kiện kinh tế - xã hội đặc biệt khó khăn, khu vực biên giới, hải đảo; Thiếu tá, Đại uý trong các lực lượng vũ trang.
Các căn hộ chung cư loại 5 có diện tích sử dụng từ 25 – 45 m2 tại khu vực đô thị hoặc căn nhà loại 3 tại khu vực nông thôn có diện tích sử dụng 40 - 45 m2 được bố tr
Advanta is a professional services firm established in 2004 that provides project execution services to healthcare organizations. It has a national presence with headquarters in California and 5 satellite offices. Advanta's team consists of experienced consultants with minimum 15 years experience who are skilled in healthcare operations, business systems, and project management. Advanta follows a results-driven transformation model to assess needs, transform processes and operations, and sustain benefits. It offers services including project leadership, process improvement, and revenue cycle management. Notable clients include government agencies like VA and private insurers. Sample projects include systems implementations, organizational redesigns, and program management support.
Epam BI - Near Realtime Marketing Support SystemDmitry Tolpeko
This document provides an overview of an implementation of a near real-time marketing support system. It includes:
1) Stream processing of log data from various sources like ad exchanges and publishers to join with contextual data for near real-time visualization and analysis of ad campaign performance. This helps improve campaigns.
2) Machine learning models are used to recognize profitable users based on their behaviors in order to target ads. Models are trained on historical user data and evaluate predictions.
3) A bidding system allows targeting ads to specific regions, demographics and interests in real-time based on streaming user data within defined budgets.
4) Social network crawling extracts event and user information for additional audience targeting opportunities.
Wingecarribee Shire Council is holding a public hearing to categorise the community land known as Corbett Gardens. The hearing is being held to comply with the Local Government Act 1993, which requires that all public land be classified as either operational or community land, and that a Plan of Management be prepared for community land. Corbett Gardens is proposed to be categorised as a park and general community use area. The community is invited to provide submissions on the proposed categories by July 10 to inform the Plan of Management for Corbett Gardens.
Innovators Jumpstart 2015-Booking for Small Businesses PlanetHatch
This document discusses consulting services and tax preparation. It suggests that everyone has consulting expertise in something and asks if this applies to the reader. It then offers to take over consulting and tax duties, mentioning services for taxes, sales tax, and determining employee versus subcontractor status. Record keeping is discussed as one of many bookkeeping issues that can be addressed. Positive feedback is also mentioned.
46/2015/NĐ-CP về quản lý chất lượng công trình xây dựngMèo Hoang
Nghị định này hướng dẫn Luật Xây dựng về quản lý chất lượng công trình xây dựng trong công tác khảo sát, thiết kế, thi công xây dựng; về bảo trì công trình xây dựng và giải quyết sự cố công trình xây dựng.
The document outlines Marty Coleman's presentation at SXSW 2014 on creating compelling images for social media. The presentation schedule includes introductory and wrap-up sessions as well as times for photographing, discussing, and critiquing images. The document discusses pros and cons of images on social media, tips for portraits and visual composition, and strategies for asking permission before photographing strangers. It also provides guidance on selecting the right social media platform based on goals and naming files for organization.
Innovators Jumpstart 2015-NBIF (The Perfect Pitch)PlanetHatch
The document provides guidance on pitching investments to NBIF. It discusses NBIF's focus on innovation investments in New Brunswick and evaluates business plans based on the product, market, finances, competitive advantage, and management team. The document emphasizes that effective pitches are concise, focus on benefits over features, and address the audience's interests. Pitches should clearly present the problem being solved, the solution, market size, and path to profitability.
This document describes using in-place computing on PostgreSQL to perform statistical analysis directly on data stored in a PostgreSQL database. Key points include:
- An F-test is used to compare the variances of accelerometer data from different phone models (Nexus 4 and S3 Mini) and activities (walking and biking).
- Performing the F-test directly in PostgreSQL via SQL queries is faster than exporting the data to an R script, as it avoids the overhead of data transfer.
- PG-Strom, an extension for PostgreSQL, is used to generate CUDA code on-the-fly to parallelize the variance calculations on a GPU, further speeding up the F-test.
The document discusses using MongoDB as a log collector. It provides an agenda that includes who the presenter is, how logging is currently done, and ideas for using MongoDB for logging in the future. Specific topics covered include using syslog-ng to send logs to MongoDB, examples of logging Apache traffic, and map-reduce examples for analyzing logs like finding the top 10 IP addresses.
Webscale PostgreSQL - JSONB and Horizontal Scaling StrategiesJonathan Katz
All data is relational and can be represented through relational algebra, right? Perhaps, but there are other ways to represent data, and the PostgreSQL team continues to work on making it easier and more efficient to do so!
With the upcoming 9.4 release, PostgreSQL is introducing the "JSONB" data type which allows for fast, compressed, storage of JSON formatted data, and for quick retrieval. And JSONB comes with all the benefits of PostgreSQL, like its data durability, MVCC, and of course, access to all the other data types and features in PostgreSQL.
How fast is JSONB? How do we access data stored with this type? What can it do with the rest of PostgreSQL? What can't it do? How can we leverage this new data type and make PostgreSQL scale horizontally? Follow along with our presentation as we try to answer these questions.
Just a few years ago all software systems were designed to be monoliths running on a single big and powerful machine. But nowadays most companies desire to scale out instead of scaling up, because it is much easier to buy or rent a large cluster of commodity hardware then to get a single machine that is powerful enough. In the database area scaling out is realized by utilizing a combination of polyglot persistence and sharding of data. On the application level scaling out is realized by microservices. In this talk I will briefly introduce the concepts and ideas of microservices and discuss their benefits and drawbacks. Afterwards I will focus on the point of intersection of a microservice based application talking to one or many NoSQL databases. We will try and find answers to these questions: Are the differences to a monolithic application? How to scale the whole system properly? What about polyglot persistence? Is there a data-centric way to split microservices?
- The document discusses strategies for analyzing large datasets that are too big to fit into memory, including using cloud computing, the ff and rsqlite packages in R, and sampling with the data.sample package.
- The ff and rsqlite packages allow working with data beyond RAM limits but require rewriting code, while data.sample provides sampling without rewriting code but introduces sampling error.
- Cloud computing avoids rewriting code and has no memory limits but requires setup, and sampling is good for analysis but not reporting exact values.
The document discusses loading data into Spark SQL and the differences between DataFrame functions and SQL. It provides examples of loading data from files, cloud storage, and directly into DataFrames from JSON and Parquet files. It also demonstrates using SQL on DataFrames after registering them as temporary views. The document outlines how to load data into RDDs and convert them to DataFrames to enable SQL querying, as well as using SQL-like functions directly in the DataFrame API.
The document provides an agenda for a presentation on getting expertise with MongoDB design patterns. It includes sections on MongoDB recap, how MongoDB works, the _id field, query execution order, indexes, replication, sharding, and introduces the presenters.
Giovanni Lanzani – SQL & NoSQL databases for data driven applications - NoSQL...NoSQLmatters
1. The document discusses challenges in building real-time, data-driven applications including dealing with big data, privacy concerns, performing some real-time analysis, and enabling real-time retrieval of large datasets.
2. It describes using Hadoop to store, enrich, and preprocess raw logs totaling around 40TB of data, while addressing privacy needs.
3. The author details techniques used to enable fast real-time retrieval of data points within a given date range and radius from a center location, such as indexing data and using temporary tables.
Introduces the use of JSON-Like data structures within DivConq. Includes how to create and access the structures within Java, as well as how to declare structures in dcSchema for data validation.
Prestogres is a PostgreSQL protocol gateway for Presto that allows Presto to be queried using standard BI tools through ODBC/JDBC. It works by rewriting queries at the pgpool-II middleware layer and executing the rewritten queries on Presto using PL/Python functions. This allows Presto to integrate with the existing BI tool ecosystem while avoiding the complexity of implementing the full PostgreSQL protocol. Key aspects of the Prestogres implementation include faking PostgreSQL system catalogs, handling multi-statement queries and errors, and security definition. Future work items include better supporting SQL syntax like casts and temporary tables.
Map visualization using D3 js and Topojson File Format. Meclenburg county Zip Codes are shown with a overlay of per-capita income and (arbitrary) number of Starbucks.
Working with JSON Data in PostgreSQL vs. MongoDBScaleGrid.io
In this post, we are going to show you tips and techniques on how to effectively store and index JSON data in PostgreSQL vs. MongoDB. Learn more in the blog post: https://scalegrid.io/blog/using-jsonb-in-postgresql-how-to-effectively-store-index-json-data-in-postgresql
Lessons Learned While Scaling Elasticsearch at VintedDainius Jocas
This document discusses lessons learned from scaling Elasticsearch at Vinted, an online second-hand marketplace. It describes the Elasticsearch cluster in early 2020 with over 400 nodes handling 300k requests per minute and 160 million documents. Performance issues included high latency and slow queries during peaks. The document then details optimizations made around indexing IDs as keywords instead of integers, using timestamps instead of date math, and replacing expensive function_score queries with distance_feature queries. It concludes with the improved 2021 cluster handling over 1 million requests per minute on 3 clusters of 160 nodes each, with dedicated staff and testing to support ongoing growth.
This document provides a summary of PostgreSQL including:
- An introduction to PostgreSQL as an open source object-relational database management system that can handle large volumes of data with high reliability.
- Details on programming languages supported in PostgreSQL like C, PL/pgSQL, Python, and R.
- Examples of large organizations that use PostgreSQL like Instagram, OpenStreetMap, and Reddit.
- An overview of PostgreSQL's data structures including schemas, catalogs, tables, functions, operators, and triggers.
- Information on managing a PostgreSQL database including configuration files, roles, and connections.
In this session, I will discuss some of the practical uses of JSON in MySQL, focusing on version 5.7 but also discussing options for previous versions, and briefly discussing MySQL 8.0. I will discuss several specific use cases, as well as some JSON antipatterns that should be avoided.
Some topics I will address:
- The evolution of JSON parsing in MySQL: from stored routines to UDFs to native functions
- Real-life use cases: Custom fields, flexible rollups, nested objects, etc.
- The power of JSON + virtual columns
- Storing JSON as text versus using new JSON data types
- Read/write balance considerations
- Disk storage implications
- Indexing JSON documents in MySQL
- Additional JSON features in MySQL 8.0
This document summarizes Doug Cutting's presentation on using Hadoop for scalable web crawling and indexing with the Nutch project. It describes how Nutch algorithms like crawling, parsing, link inversion, and indexing were converted to MapReduce jobs that can scale to billions of web pages. The document outlines the key Nutch algorithms and how they were adapted to the Hadoop framework using MapReduce.
This document discusses using MongoDB as a log collector. It provides examples of storing log data from syslog-ng in MongoDB collections, including filtering and parsing logs. It also gives examples of analyzing the log data through map-reduce to find top IP addresses and provides ideas for other uses like CAPTCHAs, error localization, and analytics.
2016 foss4 g track: developing and implementing spatial etl processes with...GIS in the Rockies
This document discusses developing and implementing spatial ETL processes using open source tools like PostGIS, Python, and cron jobs. Key points include replacing ArcSDE with PostGIS for development and QA, building Python ETL scripts to extract data from SQL Server and PostGIS, transform it using PostGIS functions, and load it into PostGIS and SQL Server, and deploying the ETL processes on an Ubuntu server with cron jobs to run daily. The goal is to break dependencies on proprietary tools and build fully open source and automated spatial ETL.
This document provides an introduction and overview of MongoDB. It begins with defining what a database and NoSQL database are. MongoDB is introduced as a popular open-source document-oriented NoSQL database that stores data in BSON documents. The document outlines some key advantages of MongoDB like its flexibility and support for many programming languages. It then covers how to set up a local MongoDB server, perform basic CRUD operations, and query documents. Finally, it introduces MongoDB Atlas as a cloud database service that handles deploying and managing MongoDB in the cloud.
Superpower Your Apache Kafka Applications Development with Complementary Open...Paul Brebner
Kafka Summit talk (Bangalore, India, May 2, 2024, https://events.bizzabo.com/573863/agenda/session/1300469 )
Many Apache Kafka use cases take advantage of Kafka’s ability to integrate multiple heterogeneous systems for stream processing and real-time machine learning scenarios. But Kafka also exists in a rich ecosystem of related but complementary stream processing technologies and tools, particularly from the open-source community. In this talk, we’ll take you on a tour of a selection of complementary tools that can make Kafka even more powerful. We’ll focus on tools for stream processing and querying, streaming machine learning, stream visibility and observation, stream meta-data, stream visualisation, stream development including testing and the use of Generative AI and LLMs, and stream performance and scalability. By the end you will have a good idea of the types of Kafka “superhero” tools that exist, which are my favourites (and what superpowers they have), and how they combine to save your Kafka applications development universe from swamploads of data stagnation monsters!
The Role of DevOps in Digital Transformation.pdfmohitd6
DevOps plays a crucial role in driving digital transformation by fostering a collaborative culture between development and operations teams. This approach enhances the speed and efficiency of software delivery, ensuring quicker deployment of new features and updates. DevOps practices like continuous integration and continuous delivery (CI/CD) streamline workflows, reduce manual errors, and increase the overall reliability of software systems. By leveraging automation and monitoring tools, organizations can improve system stability, enhance customer experiences, and maintain a competitive edge. Ultimately, DevOps is pivotal in enabling businesses to innovate rapidly, respond to market changes, and achieve their digital transformation goals.
Boost Your Savings with These Money Management AppsJhone kinadey
A money management app can transform your financial life by tracking expenses, creating budgets, and setting financial goals. These apps offer features like real-time expense tracking, bill reminders, and personalized insights to help you save and manage money effectively. With a user-friendly interface, they simplify financial planning, making it easier to stay on top of your finances and achieve long-term financial stability.
WWDC 2024 Keynote Review: For CocoaCoders AustinPatrick Weigel
Overview of WWDC 2024 Keynote Address.
Covers: Apple Intelligence, iOS18, macOS Sequoia, iPadOS, watchOS, visionOS, and Apple TV+.
Understandable dialogue on Apple TV+
On-device app controlling AI.
Access to ChatGPT with a guest appearance by Chief Data Thief Sam Altman!
App Locking! iPhone Mirroring! And a Calculator!!
14 th Edition of International conference on computer visionShulagnaSarkar2
About the event
14th Edition of International conference on computer vision
Computer conferences organized by ScienceFather group. ScienceFather takes the privilege to invite speakers participants students delegates and exhibitors from across the globe to its International Conference on computer conferences to be held in the Various Beautiful cites of the world. computer conferences are a discussion of common Inventions-related issues and additionally trade information share proof thoughts and insight into advanced developments in the science inventions service system. New technology may create many materials and devices with a vast range of applications such as in Science medicine electronics biomaterials energy production and consumer products.
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DECODING JAVA THREAD DUMPS: MASTER THE ART OF ANALYSISTier1 app
Are you ready to unlock the secrets hidden within Java thread dumps? Join us for a hands-on session where we'll delve into effective troubleshooting patterns to swiftly identify the root causes of production problems. Discover the right tools, techniques, and best practices while exploring *real-world case studies of major outages* in Fortune 500 enterprises. Engage in interactive lab exercises where you'll have the opportunity to troubleshoot thread dumps and uncover performance issues firsthand. Join us and become a master of Java thread dump analysis!
Stork Product Overview: An AI-Powered Autonomous Delivery FleetVince Scalabrino
Imagine a world where instead of blue and brown trucks dropping parcels on our porches, a buzzing drove of drones delivered our goods. Now imagine those drones are controlled by 3 purpose-built AI designed to ensure all packages were delivered as quickly and as economically as possible That's what Stork is all about.
A Comprehensive Guide on Implementing Real-World Mobile Testing Strategies fo...kalichargn70th171
In today's fiercely competitive mobile app market, the role of the QA team is pivotal for continuous improvement and sustained success. Effective testing strategies are essential to navigate the challenges confidently and precisely. Ensuring the perfection of mobile apps before they reach end-users requires thoughtful decisions in the testing plan.
Orca: Nocode Graphical Editor for Container OrchestrationPedro J. Molina
Tool demo on CEDI/SISTEDES/JISBD2024 at A Coruña, Spain. 2024.06.18
"Orca: Nocode Graphical Editor for Container Orchestration"
by Pedro J. Molina PhD. from Metadev
The Comprehensive Guide to Validating Audio-Visual Performances.pdfkalichargn70th171
Ensuring the optimal performance of your audio-visual (AV) equipment is crucial for delivering exceptional experiences. AV performance validation is a critical process that verifies the quality and functionality of your AV setup. Whether you're a content creator, a business conducting webinars, or a homeowner creating a home theater, validating your AV performance is essential.
Why Apache Kafka Clusters Are Like Galaxies (And Other Cosmic Kafka Quandarie...Paul Brebner
Closing talk for the Performance Engineering track at Community Over Code EU (Bratislava, Slovakia, June 5 2024) https://eu.communityovercode.org/sessions/2024/why-apache-kafka-clusters-are-like-galaxies-and-other-cosmic-kafka-quandaries-explored/ Instaclustr (now part of NetApp) manages 100s of Apache Kafka clusters of many different sizes, for a variety of use cases and customers. For the last 7 years I’ve been focused outwardly on exploring Kafka application development challenges, but recently I decided to look inward and see what I could discover about the performance, scalability and resource characteristics of the Kafka clusters themselves. Using a suite of Performance Engineering techniques, I will reveal some surprising discoveries about cosmic Kafka mysteries in our data centres, related to: cluster sizes and distribution (using Zipf’s Law), horizontal vs. vertical scalability, and predicting Kafka performance using metrics, modelling and regression techniques. These insights are relevant to Kafka developers and operators.
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2. so much database
I’m Aleck
mainly: django + python + js
github.com/alecklandgraf
@aleck_landgraf
aleck@buildingenergy.com
I’m Gavin
github.com/gmcquillan
@gmcquillan
3. our use case
people want to load their data…
… and play with it:
- django app for managing building data
- unstructured data
- relational data
- orgs/perms/projects
- utility meter ts data
4. we have unstructured data
- lack of fixed schema
- can create new fields without DB migration
- 2,000 fields in the standard ontology
- business logic (MCM) to map raw data to an
ontology if possible
- other logic to keep track of keys
- different for each user or organization
5. we have relational data
- everything we load relates to everything else
in the system
- buildings → organizations → permissions
- buildings → utilities → meters → ts data
- building v12010 → building v22011
6. unstructured and relational data
- django can connect to mongo
- django can connect to postgres
- complex
- is there something better?
7. PostgreSQL 9.2+ JSON type
- native type for JSON (9.4+ jsonb)
- GIN index, soon GiST index
- supports search and lookup
- easy to convert python dict to json
- json is the de facto standard for web APIs
8. why not mongo *
- MongoDB doesn’t seem to be more
performant than PostgreSQL.
- And you still get all of PostgreSQL’s goodies.
- Larger documents will probably continue to
favor PostgreSQL.
- As will larger tables.
*from Christophe Pettus’ talk at OSCON ‘13
9. did someone say django app?
- are you ready to get beta
- django-pgjson (version 0.2.0, 2014-09-13)
- works best with dev postgres 9.4 and Django
1.7+
- in beta development
- also a kickstarter project to help build some of
this out
10. setting up your django model
from django.db import models
from django_pgjson.fields import JsonField
class Something(models.Model):
name = models.CharField(max_length=32)
data = JsonField()
12. what about order_by and distinct?
- unsupported until PSQL 9.4 with jsonb
- we wrote our own inside a custom queryset
if order_by not in known_columns:
qs = list(qs)
qs.sort(
key=lambda x: getattr(x, field).get(order_by),
reverse=order_by_rev
)
13. JSON value order_by in SQL
SELECT id, NULLIF(extra_data->>'Total GHG Emissions (MtCO2e)',
'')::float AS ghg_emissions from seed_buildingsnapshot WHERE
extra_data->>'Total GHG Emissions (MtCO2e)' != '' ORDER BY
NULLIF(extra_data->>'Total GHG Emissions (MtCO2e)', '')::float
DESC LIMIT 10;
Django order_by doesn’t
work on ‘non-model-fields’
14. order_by
- can also push it to Postgres with a PL script
- http://hyperthese.net/post/sorting-json-fields-in-
postgresql/
- jsonb support in Postgres 9.4 for this, but not
for json
16. who is using this?
With JSONB and other enhancements in 9.4 "we
now have full document storage and awesome
performance with little effort," explained Craig
Kerstiens, a developer at Salesforce-backed
Heroku, in a personal blog post.