Tag: JSON

Feed: MariaDB Knowledge Base Article Feed. Author: . Rowid filtering is an optimization in MariaDB 10.4. Its target use case is as follows: a table uses ref access on index IDX1 but it also has a fairly restrictive range predicate on another index IDX2. In this case, it is advantageous to: Do an index-only scan on index IDX2 and collect rowids of index records into a data structure that allows filtering (let's call it $FILTER). When doing ref access on IDX1, check $FILTER before reading the full record Example Consider a query SELECT ... FROM orders JOIN lineitem ON o_orderkey=l_orderkey ... Read More

Feed: AWS Big Data Blog. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud that offers fast query performance using the same SQL-based tools and business intelligence applications that you use today. Many customers also like to use Amazon Redshift as an extract, transform, and load (ETL) engine to use existing SQL developer skillsets, to quickly migrate pre-existing SQL-based ETL scripts, and—because Amazon Redshift is fully ACID-compliant—as an efficient mechanism to merge change data from source data systems.In this post, I show how to use AWS Step Functions and AWS Glue Python Shell to orchestrate tasks ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Aaron Burciaga. We live in a world driven by insights and decision making fueled by data and analytics. Information and technologies are so ubiquitous that no organization needs to be a digital titan (such as Amazon or Google) to compete in today’s world of business. Companies, large and small, are recognizing the need to utilize the full value of their enterprise data to obtain an essential competitive edge. Since business competition can be fierce, it is now, more than ever, necessary for a company to be able to adeptly appropriate data assets ... Read More

Feed: Recent Announcements. You can now compare and view differences between two notebooks that are version controlled with Git in SageMaker. Jupyter notebooks (which SageMaker notebooks are built upon) are stored as JSON documents which include tags and metadata, making it difficult to diff with traditional line-by-line text diffing tools.   ... Read More

Feed: AWS Government, Education, & Nonprofits Blog. Author: AWS Public Sector Blog Team. Oxford University Press (OUP) is a department of the University of Oxford and the largest university press in the world. In 2015, OUP launched the Oxford Global Languages (OGL) initiative aiming to build lexical resources for 100 of the world’s languages and make them freely available online. A special focus is reserved to digitally under-represented languages (languages spoken by millions of native speakers, but whose lexical resources on the Internet may be of poor quality or unavailable). To date, OUP has launched 20 language websites, which include ... Read More

Feed: The Internet of Things on AWS – Official Blog. Author: Dr. Markus Bestehorn. Gaining access to sensor data or telemetry of industrial machines is a key requirement for implementing high-value use cases around smart manufacturing or Industry 4.0. For instance, predictive maintenance or automated quality control is not possible without having such data at a high temporal resolution.Given the heterogeneous environment of modern industrial production lines with many different machine types, it’s difficult to access machine data because the machines’ interfaces may use different protocols. This post provides a detailed look at the conversion of industrial protocols and extracting ... Read More

Feed: Planet PostgreSQL. While managing a small team of development resources working on PostgreSQL development, I sometimes get resources in my team that have good development experience but are new to PostgreSQL. I have developed a short set of training instructions in order to get these resources started with PostgreSQL and get them to familiarise themselves with Postgres and its internals. The purpose of this blog is to share these instructions so it can benefit others in a similar situation. The instructions involve going through a lot of documentation, white-papers, online books, it also includes few development exercises that can ... Read More

Feed: R-bloggers. Author: Marcin Dubel. TL;DR Two methods for keeping your Shiny app organized while avoiding hardcoding. Softcoding Constants in a Shiny App They can be found everywhere. Text on buttons, urls to be linked, some numeric thresholds, a font to be used on ggplot, technical IDs to business names mapping, column names from datasets… We are all (at least try to be) good programmers and we do not want to hardcode those values in the code. You can imagine the inconvenience of searching for them throughout the code when modification is implemented. And you always miss something that slightly ... Read More

Feed: R-bloggers. Author: Business Science. ## {html_document} ## ## [1] nn Bikes | Specialized.comn2. Get the Raw Data Use Chrome DevTools to locate the product information. In our case, there is a JSON-like dictionary containing what we need.2.1 Locate Data with Chrome DevTools Find the data by using the hover tool. 2.2 Find Product Data Nodes Find the nodes where the product data lives. 2.3 Filter HTML to Isolate Nodes Copy and paste the class into the html_nodes() function from the rvest library. html %>% html_nodes(".product-list__item-wrapper") 2.4 Find the Attribute That Contains the Data Extract the attributes with the html_attr() ... Read More

Feed: Planet MySQL; Author: MyDBOPS;                                    Recently, One of our client reached our Remote DBA team with a requirement to reduce the size of the table as it is having many text columns with huge number of records. At preliminary check , I have validated the table size and its row format, as it was  in compressed  format already.  Later I checked on other possibilities to compress the text columns further, At that time, then I came across per-column compression feature in Percona MySQL ... Read More