Add PEV2

src/data/roadmaps/postgresql-dba/content/111-troubleshooting-techniques/103-query-analysis/102-pev.md

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-# Pev - A PostgreSQL Explain Visualizer
-
-As you delve deeper into query analysis, it becomes important to understand and visualize the execution plans of your queries. One highly recommended tool for this purpose is `pev`, short for **PostgreSQL Explain Visualizer**.
-
-Pev is an open-source, web-based platform that takes the output of the `EXPLAIN` or `EXPLAIN ANALYZE` command and turns it into an intuitive and interactive graphical representation, allowing you to better understand and optimize query performance.
-
-## Features
-- Color-coded nodes for intuitive understanding of scan types and costs
-- Detailed information on each node with metrics like duration, loops, cost, and rows
-- Zoom in and out for easy navigation through complex plans
-- Supports various output formats (JSON, YAML, and XML)
-
-## Using Pev
-
-In order to use Pev, follow these steps:
-
-- Run your query with the `EXPLAIN` or `EXPLAIN ANALYZE` command in PostgreSQL to generate the query execution plan.
-   
-   ```
-   EXPLAIN (FORMAT JSON) SELECT * FROM my_table WHERE id = 1;
-   ```
-
-- Copy the resulting JSON output.
-
-- Head to the [Pev online visualizer](https://tatiyants.com/pev/) (or a [local instance](https://github.com/AlexTatiyants/pev) if you prefer) and paste the JSON output into the text box.
-
-- Pev will automatically generate an interactive, graphical representation of your query's execution plan to better comprehend the query's cost breakdown and any potential bottlenecks.
-
-## Example:
-
-Here's a sample of how Pev represents an execution plan. Note the easily distinguishable scan types with color-coding, and how the tooltips provide additional details when hovering over nodes.
-
-![Pev Example](https://tatiyants.com/pev/img/tooltip.png)
-
-## Summary
-
-In conclusion, Pev is an essential tool for any PostgreSQL developer looking to analyze and optimize their queries. By providing a clear visual representation of query execution plans, it enables you to quickly spot areas of improvement and ensure the overall efficiency of your database operations.

src/data/roadmaps/postgresql-dba/content/111-troubleshooting-techniques/103-query-analysis/102-pev2.md

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+# PEV2
+
+`pev2`, or *Postgres Explain Visualizer v2*, is an open-source tool designed to make query analysis with PostgreSQL easier and more understandable. By providing a visual representation of the `EXPLAIN ANALYZE` output, `pev2` simplifies query optimization by displaying the query plan and execution metrics in a readable structure. In this section, we cover the key features of `pev2` and explore how it assists in query analysis.
+
+* **Visual Representation**: `pev2` converts the raw text output of an `EXPLAIN ANALYZE` query into an interactive and color-coded tree structure that is easy to understand at a glance.
+
+* **Query Plan Metrics**: The tool provides useful execution metrics, such as the query's total execution time, processing steps, and related node costs.
+
+* **Powerful Interactivity**: Hovering over specific nodes in the visual representation displays additional information, like the time spent on a specific step or the number of rows processed.
+
+* **Indented JSON Support**: `pev2` supports indented JSON parsing, making it easier to read and understand the plan for large and complex queries.
+
+* **Save and Share Plans**: The tool allows you to save your query plans as a URL, facilitating easy sharing with your colleagues.
+
+To use `pev2`, follow these steps:
+1. Run your `EXPLAIN ANALYZE` query in your preferred PostgreSQL client.
+2. Copy the output text.
+3. Visit [https://explain.depesz.com/](https://explain.depesz.com/).
+4. Paste the copied output in the text box and click "Explain."
+5. Explore the visual representation of the query plan and analyze your query's performance.
+
+Now that you are familiar with `pev2`, use it to better understand and optimize your PostgreSQL queries. Remember, fine-tuning your queries can significantly improve performance and ensure a seamless experience for end-users. Happy optimizing!