Optimize Query of big data tables

The first thing we think of is creating an index. Creating an index can multiply the query efficiency and save time. However, if the data volume is too large, simply creating an index at this time will not help. We know that if we count queries in large data volumes, this attribute can be used to classify the created index. In this way, the query speed will be doubled or higher. However, the only drawback is that the compressed index can only be created manually. For those, if you write a class that imitates the subquery effect, you will find that the compression index is terrible, we can use joint queries or external connection queries, which is much faster than subqueries. : When Using indexes, note the following :! This will invalidate the index. If you do not use the conditions, adding a handler to the field will not use the index of the column. If you do not use the index, or if you do not use the index, you will not use the index.