Multiple sql statements or loops and conditions - php

Question

I have two tables employee and attendance.
employee : empID, empName
attendance: attendanceID, empID, date, inTime, outTime
I need to show these data in a grid where employee name in the left side and then dates. So the column headers would be like Emp Name, 1,2,3,4....,30, With or without data, number of days in the month needs to be printed.
I realized three ways to do this.
Get attendance and employee data in a join query order by empID. Then loop through the data and print it if it is matching with current date.This will go until the empID change in current loop.
Loop through employees, then loop for days in the month, in every record get attendance from the database for particular employee and particular dates.
foreach($employees as $emp)
{
$empID = $emp['empID'];
for($day =1; $day<=$maxDaysInTheMonth $day++)
{
$attendance = getAttendanceFromDatabase($empID,$day);
}
}
To make performance better we try to minimize database connections and unnecessary loops. I like to implement the second way as it has minimum conditions and loops and code is clean. But it is making database retrieval for every employee, every day. Can someone pointout some facts for performance please.

Answer 1

Fetching records in a single query and looping through it is better. As it has to call database server a single time. For the second way - it has to call the database server multiple times which is more costlier.
Then make an associative array from the data. The index would be the empID.
After generating the array you can use it as you want.

Answer 2

Try this query
$sql="SELECT employee.empName AS empName, attendance.date AS date FROM employee,attendance WHERE employee.empID=attendance.empID";

Answer 3

As #Sougata suggest, Fetching records in a single query and looping through it is better. But keep in mind the query performance should be increased as follows:
Avoid Multiple Joins in a Single Query
Try to avoid writing a SQL query using multiple joins that includes outer joins, cross apply, outer apply and other complex sub queries. It reduces the choices for Optimizer to decide the join order and join type. Sometime, Optimizer is forced to use nested loop joins, irrespective of the performance consequences for queries with excessively complex cross apply or sub queries
Avoid Use of Non-correlated Scalar Sub Query
You can re-write your query to remove non-correlated scalar sub query as a separate query instead of part of the main query and store the output in a variable, which can be referred to in the main query or later part of the batch. This will give better options to Optimizer, which may help to return accurate cardinality estimates along with a better plan.
Creation and Use of Indexes
We are aware of the fact that Index can magically reduce the data retrieval time but have a reverse effect on DML operations, which may degrade query performance. With this fact, Indexing is a challenging task, but could help to improve SQL query performance and give you best query response time.
Create a Highly Selective Index
Selectivity define the percentage of qualifying rows in the table (qualifying number of rows/total number of rows). If the ratio of the qualifying number of rows to the total number of rows is low, the index is highly selective and is most useful. A non-clustered index is most useful if the ratio is around 5% or less, which means if the index can eliminate 95% of the rows from consideration. If index is returning more than 5% of the rows in a table, it probably will not be used; either a different index will be chosen or created or the table will be scanned.
Position a Column in an Index
Order or position of a column in an index also plays a vital role to improve SQL query performance. An index can help to improve the SQL query performance if the criteria of the query matches the columns that are left most in the index key. As a best practice, most selective columns should be placed leftmost in the key of a non-clustered index.