While putting up the SQL Inner join, which table should be defined as the left table and which one as the Right table.
Does the size of the table is a determinant in the same. Please explain.
I am asking this question from the performance/ Optimization point of View.
The answer is that for an inner join the order of tables should not strictly matter. The MySQL query optimizer will make the decision about which table should come first. The reason the order of the inner join does not matter is that the result set consists of the common records from both tables.
Related
I've been looking up some documentation about this topic here: https://dev.mysql.com/doc/refman/5.7/en/left-join-optimization.html
But I don't understand the following example:
The join optimizer calculates the order in which to join tables. The table read order forced by LEFT JOIN or STRAIGHT_JOIN helps the join optimizer do its work much more quickly, because there are fewer table permutations to check. This means that if you execute a query of the following type, MySQL does a full scan on b because the LEFT JOIN forces it to be read before d:
SELECT *
FROM a JOIN b LEFT JOIN c ON (c.key=a.key)
LEFT JOIN d ON (d.key=a.key)
WHERE b.key=d.key;
The fix in this case is reverse the order in which a and b are listed in the FROM clause:
SELECT *
FROM b JOIN a LEFT JOIN c ON (c.key=a.key)
LEFT JOIN d ON (d.key=a.key)
WHERE b.key=d.key;
Why does the order make an optimization? Do JOIN and LEFT_JOIN execute in some order?
I suspect the first quote is not quite correct. I have seen LEFT JOIN turned into JOIN and then the tables touched in the 'wrong' order.
Anyway, don't worry about the work the optimizer needs to do. In thousands of slow JOINs, I have identified only one case where the cost of picking the order was important. And it was a case of multiple joins to a single table; yet another drawback of EAV schema. Anyway, there is a simple setting to avoid that problem.
LEFT/RIGHT/plain JOINs are semantically done left-to-right (regardless of the order the optimizer chooses to touch the tables).
If you are concerned about the ordering, you can add parentheses. For example:
FROM (a JOIN b ON ...) JOIN (c JOIN d ON ...) ON ...
If you are using "commajoin" (FROM a,b...), don't. However, its precedence changed long ago. The workaround was to add parens so that the same SQL would work in versions before and after the change.
Don't use LEFT unless you need it to get NULLs for missing 'right' rows. It just confuses readers into thinking that you expect NULLs.
This example is wrong in many ways, and it is not clear to me what it is trying to convey. Apologies for that. I will file a bug with the documentation team.
Some clarifications:
For the given query, the last LEFT JOIN will be converted to an inner join. This is because the WHERE clause, WHERE b.key=d.key, implies that d.key can not be NULL. Hence, any extra rows produced by LEFT JOIN compared to INNER JOIN would be filtered out by the WHERE clause. (The principles of this transformation is described in the paragraph following the given example.)
The ON clause of the first LEFT JOIN, ON (c.key=a.key), makes table c dependent on table a, but not table b. Hence, the only the requirement wrt join order is that table a is processed before table c. The order in which tables a and b are listed in the query, will not change that.
Tables b and d may be processed in any order, both wrt each other and wrt the other tables of the query.
This paragraph seems to recommend LEFT JOIN as a mechanism to reduce number of "table permutations to check". This is not meaningful since changing from INNER JOIN to LEFT JOIN may change the semantics of the query. For this purpose STRAIGHT_JOIN should be used instead.
For most join queries, execution time by far exceeds optimization time. Reducing the number of "table permutations to check" may cause potentially more efficient permutations to not be explored. Hence, LEFT JOIN should not be used unless it is required to get the wanted semantics.
Lets say I have the following query:
SELECT occurs.*, events.*
FROM occurs
INNER JOIN events ON (events.event_id = occurs.event_id)
WHERE event.event_state = 'visible'
Another way to do the same query and get the same results would be:
SELECT occurs.*, events.*
FROM occurs
INNER JOIN events ON (events.event_id = occurs.event_id
AND event.event_state = 'visible')
My question. Is there a real difference? Is one way faster than the other? Why would I choose one way over the other?
For an INNER JOIN, there's no conceptual difference between putting a condition in ON and in WHERE. It's a common practice to use ON for conditions that connect a key in one table to a foreign key in another table, such as your event_id, so that other people maintaining your code can see how the tables relate.
If you suspect that your database engine is mis-optimizing a query plan, you can try it both ways. Make sure to time the query several times to isolate the effect of caching, and make sure to run ANALYZE TABLE occurs and ANALYZE TABLE events to provide more info to the optimizer about the distribution of keys. If you do find a difference, have the database engine EXPLAIN the query plans it generates. If there's a gross mis-optimization, you can create an Oracle account and file a feature request against MySQL to optimize a particular query better.
But for a LEFT JOIN, there's a big difference. A LEFT JOIN is often used to add details from a separate table if the details exist or return the rows without details if they do not. This query will return result rows with NULL values for b.* if no row of b matches both conditions:
SELECT a.*, b.*
FROM a
LEFT JOIN b
ON (condition_one
AND condition_two)
WHERE condition_three
Whereas this one will completely omit results that do not match condition_two:
SELECT a.*, b.*
FROM a
LEFT JOIN b ON some_condition
WHERE condition_two
AND condition_three
Code in this answer is dual licensed: CC BY-SA 3.0 or the MIT License as published by OSI.
I'm working through the JOIN tutorial on SQL zoo.
Let's say I'm about to execute the code below:
SELECT a.stadium, COUNT(g.matchid)
FROM game a
JOIN goal g
ON g.matchid = a.id
GROUP BY a.stadium
As it happens, it produces the same output as the code below:
SELECT a.stadium, COUNT(g.matchid)
FROM goal g
JOIN game a
ON g.matchid = a.id
GROUP BY a.stadium
So then, when does it matter which table you assign at FROM and which one you assign at JOIN?
When you are using an INNER JOIN like you are here, the order doesn't matter. That is because you are connecting two tables on a common index, so the order in which you use them is up to you. You should pick an order that is most logical to you, and easiest to read. A habit of mine is to put the table I'm selecting from first. In your case, you're selecting information about a stadium, which comes from the game table, so my preference would be to put that first.
In other joins, however, such as LEFT OUTER JOIN and RIGHT OUTER JOIN the order will matter. That is because these joins will select all rows from one table. Consider for example I have a table for Students and a table for Projects. They can exist independently, some students may have an associated project, but not all will.
If I want to get all students and project information while still seeing students without projects, I need a LEFT JOIN:
SELECT s.name, p.project
FROM student s
LEFT JOIN project p ON p.student_id = s.id;
Note here, that the LEFT JOIN refers to the table in the FROM clause, so that means ALL of students were being selected. This also means that p.project will be null for some rows. Order matters here.
If I took the same concept with a RIGHT JOIN, it will select all rows from the table in the join clause. So if I changed the query to this:
SELECT s.name, p.project
FROM student s
RIGHT JOIN project p ON p.student_id = s.id;
This will return all rows from the project table, regardless of whether or not it has a match for students. This means that in some rows, s.name will be null. Similar to the first example, because I've made project the outer joined table, p.project will never be null (assuming it isn't in the original table). In the first example, s.name should never be null.
In the case of outer joins, order will matter. Thankfully, you can think intuitively with LEFT and RIGHT joins. A left join will return all rows in the table to the left of that statement, while a right join returns all rows from the right of that statement. Take this as a rule of thumb, but be careful. You might want to develop a pattern to be consistent with yourself, as I mentioned earlier, so these queries are easier for you to understand later on.
When you only JOIN 2 tables, usually the order does not matter: MySQL scans the tables in the optimal order.
When you scan more than 2 tables, the order could matter:
SELECT ...
FROM a
JOIN b ON ...
JOIN c ON ...
Also, MySQL tries to scan the tables in the fastest way (large tables first). But if a join is slow, it is possible that MySQL is scanning them in a non-optimal order. You can verify this with EXPLAIN. In this case, you can force the join order by adding the STRAIGHT_JOIN keyword.
The order doesn't always matter, I usually just order it in a way that makes sense to someone reading your query.
Sometime order does matter. Try it with LEFT JOIN and RIGHT JOIN.
In this instance you are using an INNER JOIN, if you're expecting a match on a common ID or foreign key, it probably doesn't matter too much.
You would however need to specify the tables the correct way round if you were performing an OUTER JOIN, as not all records in this type of join are guaranteed to match via the same field.
yes, it will matter when you will user another join LEFT JOIN, RIGHT JOIN
currently You are using NATURAL JOIN that is return all tables related data, if JOIN table row not match then it will exclude row from result
If you use LEFT / RIGHT {OUTER} join then result will be different, follow this link for more detail
I'm new to SQL and am having trouble understanding why there's a FROM keyword in a JOIN statement if I use dot notation to select the tables.columns that I want. Does it matter which table I choose out of the two? I didn't see any explanation for this in w3schools definition on which table is the FROM table. In the example below, how do I know which table to choose for the FROM? Since I essentially already selected which table.column to select, can it be either?
For example:
SELECT Customers.CustomerName, Orders.OrderID
FROM Customers
INNER JOIN Orders
ON Customers.CustomerID=Orders.CustomerID
ORDER BY Customers.CustomerName;
The order doesn't matter in an INNER JOIN.
However, it does matter in LEFT JOIN and RIGHT JOIN. In a LEFT JOIN, the table in the FROM clause is the primary table; the result will contain every row selected from this table, while rows named in the LEFT JOIN table can be missing (these columns will be NULL in the result). RIGHT JOIN is similar but the reverse: rows can be missing in the table named in FROM.
For instance, if you change your query to use LEFT JOIN, you'll see customers with no orders. But if you swapped the order of the tables and used a LEFT JOIN, you wouldn't see these customers. You would see orders with no customer (although such rows probably shouldn't exist).
The from statement refers to the join not the table. The join of table will create a set from which you will be selecting columns.
For an inner join it does not matter which table is in the from clause and which is in the join clause.
For outer joins it of course does matter, as the table in the outer join is allowed to have "missing" records.
It does not matter for inner joins: the optimizer will figure out the proper sequence of reading the tables, regardless of your choice for the ordering.
For directional outer joins, it does matter, because these are not symmetric. You choose the table in which you want to keep all rows for the first FROM table in a left outer join; for the right outer join it is the other way around.
For full outer joins it does not matter again, because the tables in full outer joins are used symmetrically to each other.
In situations when ordering does not matter you pick the order to be "natural" to the reader of your SQL statement, whatever that means for your model. SQL queries very quickly become rather hard to read, so the proper ordering of your tables is important for human readers of your queries.
Well in your current example the from operator can be applied on both tables.
SELECT Customers.CustomerName, Orders.OrderID
FROM Customers,Orders
WHERE Customers.CustomerID=Orders.CustomerID
ORDER BY Customers.CustomerName;
->Will work like your code
The comma will join the two tables.
From just means which table you are retrieving data from.
In your example, you joined the two tables using different syntax.
it could also have been :
SELECT Customers.CustomerName, Orders.OrderID
FROM Orders
INNER JOIN Customers
ON Customers.CustomerID=Orders.CustomerID
ORDER BY Customers.CustomerName;
all the code written will generate same results
I did not write this query. I am working on someone else's old code. I am looking into changing what is needed for this query but if I could simply speed up this query that would solve my problem temporarily. I am looking at adding indexes. when I did a show indexes there are so many indexes on the table orders can that also slow down a query?
I am no database expert. I guess I will learn more from this effort. :)
SELECT
orders.ORD_ID,
orders.ORD_TotalAmt,
orders.PAYMETH_ID,
orders.SCHOOL_ID,
orders.ORD_AddedOn,
orders.AMAZON_PurchaseDate,
orders.ORDSTATUS_ID,
orders.ORD_InvoiceNumber,
orders.ORD_CustFirstName,
orders.ORD_CustLastName,
orders.AMAZON_ORD_ID,
orders.ORD_TrackingNumber,
orders.ORD_SHIPPINGCNTRY_ID,
orders.AMAZON_IsExpedited,
orders.ORD_ShippingStreet1,
orders.ORD_ShippingStreet2,
orders.ORD_ShippingCity,
orders.ORD_ShippingStateProv,
orders.ORD_ShippingZipPostalCode,
orders.CUST_ID,
orders.ORD_ShippingName,
orders.AMAZON_ShipOption,
orders.ORD_ShipLabelGenOn,
orders.ORD_SHIPLABELGEN,
orders.ORD_AddressVerified,
orders.ORD_IsResidential,
orderstatuses.ORDSTATUS_Name,
paymentmethods.PAYMETH_Name,
shippingoptions.SHIPOPT_Name,
SUM(orderitems.ORDITEM_Qty) AS ORD_ItemCnt,
SUM(orderitems.ORDITEM_Weight * orderitems.ORDITEM_Qty) AS ORD_ItemTotalWeight
FROM
orders
LEFT JOIN orderstatuses ON
orders.ORDSTATUS_ID = orderstatuses.ORDSTATUS_ID
LEFT JOIN orderitems ON
orders.ORD_ID = orderitems.ORD_ID
LEFT JOIN paymentmethods ON
orders.PAYMETH_ID = paymentmethods.PAYMETH_ID
LEFT JOIN shippingoptions ON
orders.SHIPOPT_ID = shippingoptions.SHIPOPT_ID
WHERE
(orders.AMAZON_ORD_ID IS NOT NULL AND (orders.ORD_SHIPLABELGEN IS NULL OR orders.ORD_SHIPLABELGEN = '') AND orderstatuses.ORDSTATUS_ID <> 101 AND orderstatuses.ORDSTATUS_ID <> 40)
GROUP BY
orders.ORD_ID,
orders.ORD_TotalAmt,
orders.PAYMETH_ID,
orders.SCHOOL_ID,
orders.ORD_AddedOn,
orders.ORDSTATUS_ID,
orders.ORD_InvoiceNumber,
orders.ORD_CustFirstName,
orders.ORD_CustLastName,
orderstatuses.ORDSTATUS_Name,
paymentmethods.PAYMETH_Name,
shippingoptions.SHIPOPT_Name
ORDER BY
orders.ORD_ID
One simple thing you should consider is whether you really need to use left joins or you would be satisfied using inner joins for some of the joins. the new query would not be the same as the original query, so you would need to think carefully about what you really want back. If your foreign key relationships are indexed correctly, this could help substantially, especially between ORDERS and ORDERITEMS, because I would imagine these are your largest tables. The following post has a good explanation: INNER JOIN vs LEFT JOIN performance in SQL Server. There are lots of other things that can be done, but you will need to post the query plan so people can dive deeper.
It looks like just adding the index was all that was needed.
create index orderitems_ORD_ID_index on orderitems(ORD_ID);