CREATE DATABASE PortfolioDB;

USE PortfolioDB;

CREATE TABLE Certifications (
    id INT PRIMARY KEY,
    title VARCHAR(100),
    provider VARCHAR(100)
);

INSERT INTO Certifications (id, title, provider) VALUES
    (1, 'Data Science with Python', 'Internshala'),
    (2, 'Software Development BootCamp', 'Floydee Foundation'),
    (3, 'Introduction to Generative AI Studio', 'SimpliLearn')
;

FLUSH TABLES WITH READ LOCK;

UNLOCK TABLES;

LOCK TABLES Certifications WRITE;

UPDATE Certifications SET provider = 'SimpliLearn / SkillUp', title = 'Introduction to Generative AI Studio (Updated)' WHERE id = 3;

UNLOCK TABLES;

LOCK TABLES Certifications READ;

SELECT * FROM Certifications;

from pyspark.sql import SparkSession

spark = SparkSession.builder.appName("PortfolioAchievements").getOrCreate()

data = [
    (1, "Cleared the Tata Crucible Quiz Prelim Round-1 (Online Mode)"),
    (2, "Worked with Web development NGO for free as a volunteer"),
    (3, "Participated in the SQL query firing workshop")
]

columns = ["id", "achievement"]

achievements_df = spark.createDataFrame(data, columns)

rows = achievements_df.collect()

html_output = "<table border='1' cellspacing='0' cellpadding='8'>"

html_output += "<thead><tr><th>id</th><th>achievement</th></tr></thead><tbody>"

for row in rows:
    html_output += f"<tr><td>{row['id']}</td><td>{row['achievement']}</td></tr>"

html_output += "</tbody></table>"

with open("achievements.html", "w", encoding="utf-8") as f:
    f.write(html_output)

print(html_output)