chore: update roadmap content json (#8471)

Co-authored-by: kamranahmedse <4921183+kamranahmedse@users.noreply.github.com>
pull/8484/head
github-actions[bot] 5 days ago committed by GitHub
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  1. 22
      public/roadmap-content/computer-science.json
  2. 4
      public/roadmap-content/sql.json

@ -2809,26 +2809,10 @@
}
]
},
"IaPd_zuLbiOCwoSHQLoIG": {
"2-3-4-trees@IaPd_zuLbiOCwoSHQLoIG.md": {
"title": "2 3 4 Trees",
"description": "In practice: For every 2-4 tree, there are corresponding red–black trees with data elements in the same order. The insertion and deletion operations on 2-4 trees are also equivalent to color-flipping and rotations in red–black trees. This makes 2-4 trees an important tool for understanding the logic behind red–black trees, and this is why many introductory algorithm texts introduce 2-4 trees just before red–black trees, even though 2-4 trees are not often used in practice.\n\nVisit the following resources to learn more:",
"links": [
{
"title": "CS 61B Lecture 26: Balanced Search Trees",
"url": "https://archive.org/details/ucberkeley_webcast_zqrqYXkth6Q",
"type": "article"
},
{
"title": "Bottom Up 234-Trees",
"url": "https://www.youtube.com/watch?v=DQdMYevEyE4&index=4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6",
"type": "video"
},
{
"title": "Top Down 234-Trees",
"url": "https://www.youtube.com/watch?v=2679VQ26Fp4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=5",
"type": "video"
}
]
"description": "",
"links": []
},
"UOYeM-hqIKCrB9hGez4Q_": {
"title": "K-ary / M-ary Tree",

@ -1260,7 +1260,7 @@
},
"Ps9Yv2s-bKvEegGAbPsiA": {
"title": "Query Optimization",
"description": "Query optimization in SQL involves refining queries to enhance their execution speed and reduce resource consumption. Key strategies include indexing columns used in `WHERE`, `JOIN`, and `ORDER BY` clauses to accelerate data retrieval, minimizing data processed by limiting the number of columns selected and filtering rows early in the query. Using appropriate join types and arranging joins in the most efficient order are crucial. Avoiding inefficient patterns like `SELECT`, replacing subqueries with joins or common table expressions (CTEs), and leveraging query hints or execution plan analysis can also improve performance. Regularly updating statistics and ensuring that queries are structured to take advantage of database-specific optimizations are essential practices for maintaining optimal performance.\n\nLearn more from the following resources:",
"description": "Query optimization in SQL involves refining queries to enhance their execution speed and reduce resource consumption. Key strategies include indexing columns used in `WHERE`, `JOIN`, and `ORDER BY` clauses to accelerate data retrieval, minimizing data processed by limiting the number of columns selected and filtering rows early in the query. Using appropriate join types and arranging joins in the most efficient order are crucial. Avoiding inefficient patterns like `SELECT *`, replacing subqueries with joins or common table expressions (CTEs), and leveraging query hints or execution plan analysis can also improve performance. Regularly updating statistics and ensuring that queries are structured to take advantage of database-specific optimizations are essential practices for maintaining optimal performance.\n\nLearn more from the following resources:",
"links": [
{
"title": "12 Ways to Optimize SQL Queries",
@ -1495,7 +1495,7 @@
},
"UVTgbZrqpbYl1bQvQejcF": {
"title": "Reducing Subqueries",
"description": "Recursive queries in SQL allow for iterative processing of hierarchical or tree-structured data within a single query. They consist of an anchor member (the base case) and a recursive member that references the query itself, enabling the exploration of parent-child relationships, traversal of graphs, or generation of series data. This powerful feature is particularly useful for tasks like querying organizational hierarchies, bill of materials structures, or navigating complex relationships in data that would otherwise require multiple separate queries or procedural code.\n\nLearn more from the following resources:",
"description": "Reducing subqueries is a common SQL optimization technique, especially when dealing with complex logic or large datasets. Correlated subqueries, which are evaluated once for each row in the outer query, can degrade the performance. Subqueries can often be replaced with JOIN operations. In cases where subqueries are reused, consider replacing them with Common Table Expressions (CTEs), which offer modularity and avoid repeated executions of the same logic. Limiting the result set returned by subqueries and storing the results of expensive subqueries in temporary tables for reuse can also improve performance.\n\nLearn more from the following resources:",
"links": []
},
"w53CSY53nAAN0ux-XeJ4c": {

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