• Lazy write is an effect caused by the use of a write-back cache. In a write-back cache, data is first written to the cache and then is later (during a particular time such as an idle machine cycle) is written to the disk or memory.
• This type of cache is more complex to implement, due to the need to track each locations that have been written over and what needs to be marked as dirty to fix later.

Lazy writer in Memory

• Lazy writer is a thread which is present for each NUMA node (and every instance has at least one) that scans through the buffer cache associated with that node.
• The lazy writer thread sleeps for a specific interval of time, and when it wakes up, it examines the size of the free buffer list.
• If the list is below a certain threshold, which depends on the total size of the buffer pool, the lazy writer thread scans the buffer pool to repopulate the free list.
• As buffers are added to the free list, they are also written to disk if they are dirty.
• So if there is no memory pressure and memory notification is stable it sleeps
• The sole purpose of Lazy Writer is to maintain some free buffers in the SQL Server Buffer Pool.
• Lazy writer runs periodically and check which buffers can be flushed and returned to the free pool.
• So even SQL Server is not under memory pressure, it will also work regularly.

• The inner query is executed only once.
• The inner query will get executed first and the output of the inner query used by the outer query.
• The inner query is not dependent on outer query.

• The outer query will get executed first and for every row of outer query, inner query will get executed.
• So the inner query will get executed as many times as number of rows in result of the outer query.
• The outer query output can use the inner query output for comparison. This means inner query and outer query dependent on each other.

SELECT Employee_name,dept_id 
FROM Employee
WHERE Employee_name IN (SELECT Employee_name FROM dept WHERE Employee.dept_id=dept.dept_id);

• • The union operator combines the results of two or more queries into a single result set. But no.of columns must match in both/all the queries (and also the order) which are used for union.
  • We can union two tables irrespective of common field.
  • The UNION set operator is used for combining data from two tables which have columns with the same datatype.
    • Union – Returns with no duplicate rows.
    • Union all – Retruns with duplicate rows (No. of rows returned = No. of rows in Query1 + No. of rows in Query 2).

• We cannot use the union operator within a create view statement.
• We cannot use the union operator on text and image columns.

• Joins are used to extract information from more than one table based on the related column/coloums (PK and RFK) any no. of rows can be retrived based on matching colums.
• We can join two tables by ‘join’ if they have common field.
• A Join is used for displaying columns with the same or different names from different tables.
• Different types of joins are Inner join=equi join=join , outer join (Right outer join/right join, Left outer join / left join), Cross join , and full outer join/outer join.
• We can use join operator within a create view statement.
• We can use the join operator on text and image columns.

• SQLcode -501 pops up to show that , the Cursor identified in fetch or close statement is not opened.

• SQL error code means it return codes that are preceded by a minus sign (-) indicate that the SQL statement execution was unsuccessful.
  • If SQLCODE = 0, execution was successful.
  • If SQLCODE > 0, execution was successful with a warning.
  • If SQLCODE < 0, execution was not successful.
  • SQLCODE = 100, “no data” was found.

• We have two tables Wikitechy_Employee and Department. Wikitechy_Employee contains details of employees e.g. id, name, age, salary and department id, while Department contains id and department name.
• In order to show, which employee works for which department we need to join two tables on DEPT_ID to get the the department name.
• Our requirement is to find how many employees are working in each department and average salary of department.
• In order to use WHERE clause, we will only include employees who are earning more than 5000.
• Before executing our query which contains WHERE, HAVING, and GROUP BY clause, let see data from Wikitechy_Employee and Department table:

• From the number of employee (NUM_EMPLOYEE) column you can see that only Vijay who work for Marketing department is not included in result set because his earning 5000.
• This example shows that, condition in WHERE clause is used to filter rows before you aggregate them and then HAVING clause comes in picture for final filtering, which is clear from following query, now Marketing department is excluded because it doesn’t pass condition in HAVING clause i..e AVG_SALARY > 7000

• Index is a database object which improves the efficiency of the query. When queries are run against a database, an index on that database basically helps in the way the data is sorted to process the query for faster and data retrievals are much faster when we have an index.