teleren/devto huggingface dataset:
SQL: Get records having min/max value per group
Tags: mysql, sql, postgres, webdev
Published: 2024-05-24 10:32:52

Here's one possible solution for a case when you need to fetch a set of records unique on one (or several) column with a min/max value in the other column (usually a timestamp). The solution doesn't require any changes to the DB scheme (denormalization or creation of views) and can be performed in the scope of a single SQL query.

## Scenario
Imagine you have a table named `customer_subscriptions` with the following fields:

- `user_name` (we'll use name instead of `user_id` for simplicity here consider `user_name` to be unique for this example)
- `plan_name` (we'll use name instead of `plan_id` here as well)
- `created_at` (the timestamp when the subscription was created)

For illustration, consider the following data in `customer_subscriptions`:

![Sample customer_subscriptions table](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/w2x5d8fkjb6uejshsp52.png)

Let's say we want to show a table showing what was the first subscription plan for each user:

![Desired query result](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/57s5ceotrrd2roige1hg.png)

## Subquery JOIN solution

1. First, we must find the minimum `created_at` value for each user subscription entry separately in a subquery.
2. Then, we join the subquery on `user_name` and `created_at` to filter down to the first subscription record for each user.

```sql
SELECT cs.user_name, cs.plan_name, cs.created_at
FROM customer_subscriptions cs
JOIN (
    SELECT user_name, MIN(created_at) AS min_created_at
    FROM customer_subscriptions
    GROUP BY user_name
) AS sub
ON cs.user_name = sub.user_name AND cs.created_at = sub.min_created_at;
```

This solution would work perfectly for both MySQL and PostgreSQL.

## PostgreSQL-specific solution

In PostgreSQL, we can use `DISTINCT ON` to filter the resulting set to be unique on specific columns, such as `user_name`. We won't need to join an additional subquery.

1. `DISTINCT ON (user_name)`: Ensures that each `user_name` appears only once in the result set.
2. `ORDER BY user_name, created_at`: Orders the records by `user_name` and then by `created_at` within each user_name, so the first record (with the smallest `created_a`t value) is selected.

```sql
SELECT DISTINCT ON (user_name) user_name, plan_name, created_at
FROM customer_subscriptions
ORDER BY user_name, created_at;
```

## Conclusion

Fetching the first subscription record for each user based on the earliest `created_at` value can be efficiently achieved using different SQL constructs available in MySQL and PostgreSQL. While MySQL relies on subqueries and joins, PostgreSQL’s `DISTINCT ON` clause provides a straightforward and elegant solution.
Pelle Pelle Store | A Trusted & Legendary Pelle Jacket Store:
Tags: jacket, website, store, pellepelle
Published: 2024-05-24 10:32:35

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App.js Conf is live now!
Published: 2024-05-24 10:32:32

https://www.youtube.com/watch?v=s0wn7qpBoB8

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Jnanabhumi Scholarship Status Check: Registration, Login
Published: 2024-05-24 10:18:33

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Exploring the Synergy Between Development and Futures Trading in the Crypto Space
Tags: webdev, beginners, news, cryptocurrency
Published: 2024-05-24 10:07:24

In the dynamic world of cryptocurrency, the convergence of development and futures trading has emerged as a critical intersection. Developers are leveraging their expertise and innovative solutions to reshape the landscape of financial markets, particularly in the realm of futures trading.

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Looking Ahead:
As the crypto ecosystem continues to evolve, the synergy between development and futures trading is expected to grow stronger. Developers will play a key role in shaping the future of finance, driving innovation and pushing the boundaries of what is possible in the crypto market. By embracing futures trading and leveraging platforms like WhiteBIT, developers can unlock new opportunities for growth and success in the ever-changing landscape of cryptocurrency.
Bamboo products
Published: 2024-05-24 10:05:49

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All India Typing Test, Typing Skill Test, Typing Certificate, CPCT English Typing
Published: 2024-05-24 10:05:26

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Software Development Service Ahmedabad
Tags: benchkart, softwaredevelopment, b2b, services
Published: 2024-05-24 10:04:14

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[Self-Study] Achievement: Describe the core architectural components of Azure
Published: 2024-05-24 09:53:31


![Achievement Image](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/9apam4q8or3k9njpgmea.png)

Today, I learnt how to describe the following definitions in Microsoft Azure. They are:
- Resource Groups
- Availability Zones
- Region Pairs
- Subscriptions
- Management Groups

Using the Microsoft Learn Sandbox, I also learnt the steps to create an Azure Resource:
- at Microsoft Azure (portal.azure.com), I created a Virtual Machine resource
- I noticed how in the resource group of the virtual machine I created, Azure created the rest of the resources by default and associated them using similar names 

Achievement Link: [Click Here](https://learn.microsoft.com/en-us/users/theasea-4752/achievements/uxvjxsk3)
7 Must-Have Qualities to Look for When Hiring Mobile App Developers
Tags: mobile, app, developer
Published: 2024-05-24 09:49:56

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From Wikipedia, the free encyclopedia
Published: 2024-05-24 09:48:40

A book is a medium for recording information in the form of writing or images. Books are typically composed of many pages, bound together and [protected by a cover](https://en.wikipedia.org/wiki/Book).[1] Modern bound books were preceded by many other written mediums, such as the codex and the scroll. The book publishing process is the series of steps involved in their creation and dissemination.
API Development Services
Tags: unitedstates, api, apigateway, development
Published: 2024-05-24 09:48:25

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Element-Wise Numerical Operations in NumPy: A Practical Guide with Examples
Tags: python, numerical, operations, numpy
Published: 2024-05-24 09:44:48

Numeric operations in NumPy are element-wise operations performed on NumPy arrays. These operations include basic arithmetic like addition, subtraction, multiplication, and division, as well as more complex operations like exponentiation, modulus and reciprocal. Here are some examples of these operations:

**Addition**:
You can add two arrays element-wise using the `+` operator or the `np.add()` function.
```python
import numpy as np

# Define two arrays
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])

# Element-wise addition
result = np.add(a, b)  # or a + b
print(result)  

# Output: [5 7 9]
```

**Subtraction**:
Similarly, subtraction is done using the `-` operator or `np.subtract()` function.
```python
# Element-wise subtraction
result = np.subtract(a, b)  # or a - b
print(result)  

# Output: [-3 -3 -3]
```

**Multiplication**:
For element-wise multiplication, use the `*` operator or `np.multiply()`.
```python
# Element-wise multiplication
result = np.multiply(a, b)  # or a * b
print(result)  

# Output: [ 4 10 18]
```

**Division**:
Element-wise division can be performed with the `/` operator or `np.divide()`.
```python
# Element-wise division
result = np.divide(a, b)  # or a / b
print(result)  

# Output: [0.25 0.4  0.5 ]
```

**Exponentiation**:
Raise the elements of one array to the powers of another using `**` or `np.power()`.
```python
# Element-wise exponentiation
result = np.power(a, 2)  # or a ** 2
print(result)  

# Output: [1 4 9]
```

**Modulus**:
The modulus operation returns the remainder of division using `%` or `np.mod()`.
```python
# Element-wise modulus
result = np.mod(a, b)  # or a % b
print(result)  

# Output: [1 2 3]
```
**Reciprocal**:
The reciprocal of an array is obtained by taking the inverse of each element. In NumPy, you can compute the reciprocal using the `np.reciprocal()` function or the `1 / array` expression.

```python
import numpy as np

# Define an array
a = np.array([1, 2, 3])

# Element-wise reciprocal
reciprocal_result = np.reciprocal(a)  # or 1 / a
print(reciprocal_result)  

# Output: [1.         0.5        0.33333333]
```

The reciprocal of each element in the array `a` is computed as follows:
- Reciprocal of 1: 1.0
- Reciprocal of 2: 0.5
- Reciprocal of 3: approximately 0.3333 (rounded to 4 decimal places)

These operations are highly optimized in NumPy and can be performed on arrays of any size, making them very efficient for numerical computations😊.
Why Security Audits Are Crucial For Businesses
Published: 2024-05-24 09:38:44

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