My CS Journey

 Here are three important takeaways from the class: 1. An important thing I learned was how to interpret and design ER diagrams and how primary and foreign keys are used to link data from different tables. Learning this is key to understanding how companies store and update the data that is crucial to their business model.  2. It was also important to learn how to write SQL queries and JavaScript documents to  create schemas. This is one of the most essential parts of a database and includes tables, columns and constraints.  3. Finally, it was important to learn about transactions and indexing. For transactions, it was it was crucial to learn about the ACID properties of how database transactions are being processed to ensure that data is accurate and minimize failed transactions. Indexes help improve the efficiency of retrieving data which uses less resources but might also slow down writing data due to having to update the index as well. 

 Comparing MongoDB and MySQL:   Relational databases use tables with rows and columns to organize data. SQL is used to write and run queries. MongoDB stores files in JSON documents. Both support indexing however MongoDB avoids joins and used embedded documents instead. Relational databases using foreign keys and joins to link data across tables. MongoDB also only allows atomic operations, which must be fully completed or stopped all together. A system like inventory or banking would benefit from a relational database since the data needs to be structured and many relationships exist. MongoDB could be chosen when data can differ greatly between documents and efficiency is key. 

     I learned that programming languages can be grouped by how they give instructions, like telling the computer what to do or just describing what result is wanted. I also learned that SQL can be written inside other languages like Java which is called embedded SQL. There are different programming languages that are used to connect to databases using APIs. JDBC is the tool Java uses to interact with databases and it lets Java programs run SQL commands. I also learned that making a database connection in Java needs the right setup and error handling to avoid crashes.

 In this webpage "Slow Indexes, Part 1", when the author mentions a slow index, he is merely saying that the index does not provide much improvement as expected. Sometimes, an index may make queries less efficient.  If multiple rows have the same index value, then the database must read the next leaf node to see if there are more instances of the same value. Other times, looking up an index requires three steps, one of which is fetching the data. This step may require accessing many blocks, causing the index lookup to be slow.  Sometimes, a "slow index" is not caused by the index structure itself, but by how the table is accessed. This is what may be causing a less efficient data lookup process.