How to Fix Fuzzy Matching Issues in SQL Server Using Chinese_Hong_Kong_Stroke_90_CI_AS Collation
Fuzzy Match in SQL Server with Chinese_Hong_Kong_Stroke_90_CI_AS Collation When working with databases that support Unicode characters, including those used in the Chinese language, it’s not uncommon to encounter issues with fuzzy matching. This is particularly true when using collations like Chinese_Hong_Kong_Stroke_90_CI_AS, which can lead to unexpected results.
In this article, we’ll explore why fuzzy matching occurs with this collation and provide a solution to avoid these issues.
Understanding the Chinese_Hong_Kong_Stroke_90_CI_AS Collation The Chinese_Hong_Kong_Stroke_90_CI_AS collation is designed specifically for use with data that contains Traditional Chinese characters.
Converting Oracle Timestamps to ISO-8601 Date Datatype: A Step-by-Step Guide
Understanding Oracle’s Timestamp Format and Converting to ISO-8601 Date Datatype Oracle, a popular relational database management system, uses a unique timestamp format. In this article, we will explore how to convert an Oracle timestamp to the ISO-8601 date datatype.
Introduction to Oracle’s Timestamp Format Oracle’s timestamp format is based on the TIMESTAMP data type in SQL. The format for a Unix-style timestamp (e.g., 18-12-2003 13:15:00) is:
Year-month-day (YYYY-MM-DD) Hour-minute-second (HH24:MM:SS) However, when working with Oracle databases, it’s common to use the following format:
Understanding the Limitations of GROUP BY with Nested Aggregate Functions in Oracle
Understanding the Limitations of GROUP BY with Nested Aggregate Functions in Oracle Introduction When working with databases, it’s essential to understand the limitations and capabilities of various SQL functions, including aggregate functions. In this article, we’ll delve into the specific case of grouping by a nested aggregate function in Oracle, exploring why GROUP BY is necessary for such operations.
Background: Understanding Aggregate Functions Before diving into the specifics of GROUP BY, let’s take a brief look at how aggregate functions work.
Adding Equal Column Values Count in SQL Server
SQL New Column Count Equal Column Values =====================================================
In this article, we will explore how to add a new column in SQL Server that represents the count of data sets where the specified column has equal values. We’ll discuss different approaches, including using windowed aggregates and common table expressions (CTEs).
Background Information The question at hand is about taking a table with three columns (Day, Title, and Sum) and adding a new column that counts how many times the value in the Day column appears.
Setting Column Names in R's cpp11: A Guide to C++11 Features
Setting colnames in R’s cpp11 Rcpp is a popular package for creating C++ extensions to R. One of the powerful features of Rcpp is its ability to integrate C++ code with R, allowing users to leverage the performance and flexibility of C++. The cpp11 module in particular provides an interface to C++11 features within R.
In this article, we will explore how to set column names for a C++ function using cpp11.
Understanding the Root Cause of Database Connections Exhaustion in Oracle Databases: Best Practices for Performance Optimization
Understanding DB Connections Exhaustion in Oracle Databases =====================================================================================
As a technical blogger, I’ve encountered numerous issues related to database connections exhaustion. In this article, we’ll delve into the specifics of how WebLogic connection pool capacity can be underutilized while the actual database connections continue to rise, causing the maximum allowed size limit to be reached.
Background and Context In modern web applications, databases play a crucial role in storing and retrieving data efficiently.
Bulk Uploading Large JSON Files to MySQL: A Step-by-Step Guide
Overview of the Problem The problem presented involves bulk uploading a complex JSON file to a MySQL database. The JSON file contains nested data with multiple levels of structure, and its size is approximately 50 GB. We’ll explore possible solutions for this task.
Background: JSON Data Structure JSON (JavaScript Object Notation) is a lightweight data interchange format that’s widely used in web development and other applications. It consists of key-value pairs, arrays, objects, and literals.
Understanding Device Tokens in iOS: A Comprehensive Guide to Remote Notifications
Understanding Device Tokens in iOS As a developer, working with device tokens can be a challenging task. In this article, we will delve into the details of how to handle device tokens in iOS.
Overview of Device Tokens A device token is an identifier assigned to an iOS or macOS device by Apple’s push notification service, APNs (Apple Push Notification service). This token is used to identify the device and authenticate incoming push notifications.
Understanding the fbprophet Error (ValueError: lam value too large): A Guide to Resolving the Issue in Facebook Prophet
Understanding the fbprophet Error (ValueError: lam value too large) In this blog post, we’ll delve into the details of an error that occurs when using the popular forecasting library fbprophet. Specifically, we’ll explore how to resolve the ValueError: lam value too large issue.
Introduction Facebook Prophet is a software for forecasting time series data. It uses additive and multiplicative seasonality models with support for daily, weekly, monthly, year-to-date (YTD), and yearly seasonality patterns.
Understanding MySQL Triggers and Subqueries: A Powerful Combination for Complex Data Processing Tasks
Understanding MySQL Triggers and Subqueries
MySQL triggers are a powerful tool for automating database operations. They allow you to create a rule that is applied automatically every time a specific event occurs, such as an insert or update operation on a table. In this article, we will explore the concept of MySQL triggers and how they can be used in conjunction with subqueries to achieve complex data processing tasks.
Creating a MySQL Trigger