Related
i am running a stored procedure to delete data from two tables:
delete from TESTING_testresults
from TESTING_testresults
inner join TESTING_QuickLabDump
on TESTING_QuickLabDump.quicklabdumpid = TESTING_TestResults.quicklabdumpid
where TESTING_quicklabdump.[Specimen ID]=#specimen
delete from TESTING_QuickLabDump
from TESTING_Quicklabdump
where [specimen id]=#specimen
one table is 60m rows and the other is about 2m rows
the procedure takes about 3 seconds to run.
is there any way i can speed this up? perhaps using EXISTS?
meaning IF EXISTS...THEN DELETE - because the delete should not be occurring every single time
something like this
if #specimen exists in TESTING_QuickLabDump then do the procedure with the two deletes
thank you !!!
Rewriting the query probably wont help speeding this up. Use the profiler to find out which parts of the query are slow. For this, make it profiler output the execution plan. Then, try adding appropriate indexes. Perhaps one or both tables could use an index over [specimen id].
For a table with 60 mil rows I would definitely look into partitioning the data horizontally and/or vertically. If it's time-sensitive data then you ought to be able to move old data into a history table. That's usually the first and most obvious thing people do so I would imagine if that were a possibility you would have already done it.
If there are many columns then it would definitely benefit you to denormalize the data into multiple tables. If you did this, I would suggest renaming the tables and creating a view of all the partitioned tables named after the original table. Doing that should ensure existing code isn't broken.
If you 'really' want to fine tune the speed then you should look into getting a faster hard drive and learn a little about hard drives work. Whether the data is stored towards the inner or outer section of the hd will affect speed of access slightly for example. And solid state hard drives have come a long way so you might look into getting one of those.
Beside indexing "obvious" fields, also look in your database schema and check if you have any FOREIGN KEYs whose ON DELETE CASCADE or SET NULL might be triggered by your delete (unlike Oracle, MS SQL Server will tend to show these in the execution plan). Fortunately, this is usually fairly easy to fix by indexing the child endpoint of the FOREIGN KEY.
Also check if you have any expensive triggers.
I've heard that SELECT * is generally bad practice to use when writing SQL commands because it is more efficient to SELECT columns you specifically need.
If I need to SELECT every column in a table, should I use
SELECT * FROM TABLE
or
SELECT column1, colum2, column3, etc. FROM TABLE
Does the efficiency really matter in this case? I'd think SELECT * would be more optimal internally if you really need all of the data, but I'm saying this with no real understanding of database.
I'm curious to know what the best practice is in this case.
UPDATE: I probably should specify that the only situation where I would really want to do a SELECT * is when I'm selecting data from one table where I know all columns will always need to be retrieved, even when new columns are added.
Given the responses I've seen however, this still seems like a bad idea and SELECT * should never be used for a lot more technical reasons that I ever though about.
One reason that selecting specific columns is better is that it raises the probability that SQL Server can access the data from indexes rather than querying the table data.
Here's a post I wrote about it: The real reason select queries are bad index coverage
It's also less fragile to change, since any code that consumes the data will be getting the same data structure regardless of changes you make to the table schema in the future.
Given your specification that you are selecting all columns, there is little difference at this time. Realize, however, that database schemas do change. If you use SELECT * you are going to get any new columns added to the table, even though in all likelihood, your code is not prepared to use or present that new data. This means that you are exposing your system to unexpected performance and functionality changes.
You may be willing to dismiss this as a minor cost, but realize that columns that you don't need still must be:
Read from database
Sent across the network
Marshalled into your process
(for ADO-type technologies) Saved in a data-table in-memory
Ignored and discarded / garbage-collected
Item #1 has many hidden costs including eliminating some potential covering index, causing data-page loads (and server cache thrashing), incurring row / page / table locks that might be otherwise avoided.
Balance this against the potential savings of specifying the columns versus an * and the only potential savings are:
Programmer doesn't need to revisit the SQL to add columns
The network-transport of the SQL is smaller / faster
SQL Server query parse / validation time
SQL Server query plan cache
For item 1, the reality is that you're going to add / change code to use any new column you might add anyway, so it is a wash.
For item 2, the difference is rarely enough to push you into a different packet-size or number of network packets. If you get to the point where SQL statement transmission time is the predominant issue, you probably need to reduce the rate of statements first.
For item 3, there is NO savings as the expansion of the * has to happen anyway, which means consulting the table(s) schema anyway. Realistically, listing the columns will incur the same cost because they have to be validated against the schema. In other words this is a complete wash.
For item 4, when you specify specific columns, your query plan cache could get larger but only if you are dealing with different sets of columns (which is not what you've specified). In this case, you do want different cache entries because you want different plans as needed.
So, this all comes down, because of the way you specified the question, to the issue resiliency in the face of eventual schema modifications. If you're burning this schema into ROM (it happens), then an * is perfectly acceptable.
However, my general guideline is that you should only select the columns you need, which means that sometimes it will look like you are asking for all of them, but DBAs and schema evolution mean that some new columns might appear that could greatly affect the query.
My advice is that you should ALWAYS SELECT specific columns. Remember that you get good at what you do over and over, so just get in the habit of doing it right.
If you are wondering why a schema might change without code changing, think in terms of audit logging, effective/expiration dates and other similar things that get added by DBAs for systemically for compliance issues. Another source of underhanded changes is denormalizations for performance elsewhere in the system or user-defined fields.
You should only select the columns that you need. Even if you need all columns it's still better to list column names so that the sql server does not have to query system table for columns.
Also, your application might break if someone adds columns to the table. Your program will get columns it didn't expect too and it might not know how to process them.
Apart from this if the table has a binary column then the query will be much more slower and use more network resources.
There are four big reasons that select * is a bad thing:
The most significant practical reason is that it forces the user to magically know the order in which columns will be returned. It's better to be explicit, which also protects you against the table changing, which segues nicely into...
If a column name you're using changes, it's better to catch it early (at the point of the SQL call) rather than when you're trying to use the column that no longer exists (or has had its name changed, etc.)
Listing the column names makes your code far more self-documented, and so probably more readable.
If you're transferring over a network (or even if you aren't), columns you don't need are just waste.
Specifying the column list is usually the best option because your application won't be affected if someone adds/inserts a column to the table.
Specifying column names is definitely faster - for the server. But if
performance is not a big issue (for example, this is a website content database with hundreds, maybe thousands - but not millions - of rows in each table); AND
your job is to create many small, similar applications (e.g. public-facing content-managed websites) using a common framework, rather than creating a complex one-off application; AND
flexibility is important (lots of customization of the db schema for each site);
then you're better off sticking with SELECT *. In our framework, heavy use of SELECT * allows us to introduce a new website managed content field to a table, giving it all of the benefits of the CMS (versioning, workflow/approvals, etc.), while only touching the code at a couple of points, instead of a couple dozen points.
I know the DB gurus are going to hate me for this - go ahead, vote me down - but in my world, developer time is scarce and CPU cycles are abundant, so I adjust accordingly what I conserve and what I waste.
SELECT * is a bad practice even if the query is not sent over a network.
Selecting more data than you need makes the query less efficient - the server has to read and transfer extra data, so it takes time and creates unnecessary load on the system (not only the network, as others mentioned, but also disk, CPU etc.). Additionally, the server is unable to optimize the query as well as it might (for example, use covering index for the query).
After some time your table structure might change, so SELECT * will return a different set of columns. So, your application might get a dataset of unexpected structure and break somewhere downstream. Explicitly stating the columns guarantees that you either get a dataset of known structure, or get a clear error on the database level (like 'column not found').
Of course, all this doesn't matter much for a small and simple system.
Lots of good reasons answered here so far, here's another one that hasn't been mentioned.
Explicitly naming the columns will help you with maintenance down the road. At some point you're going to be making changes or troubleshooting, and find yourself asking "where the heck is that column used".
If you've got the names listed explicitly, then finding every reference to that column -- through all your stored procedures, views, etc -- is simple. Just dump a CREATE script for your DB schema, and text search through it.
Performance wise, SELECT with specific columns can be faster (no need to read in all the data). If your query really does use ALL the columns, SELECT with explicit parameters is still preferred. Any speed difference will be basically unnoticeable and near constant-time. One day your schema will change, and this is good insurance to prevent problems due to this.
definitely defining the columns, because SQL Server will not have to do a lookup on the columns to pull them. If you define the columns, then SQL can skip that step.
It's always better to specify the columns you need, if you think about it one time, SQL doesn't have to think "wtf is *" every time you query. On top of that, someone later may add columns to the table that you actually do not need in your query and you'll be better off in that case by specifying all of your columns.
The problem with "select *" is the possibility of bringing data you don't really need. During the actual database query, the selected columns don't really add to the computation. What's really "heavy" is the data transport back to your client, and any column that you don't really need is just wasting network bandwidth and adding to the time you're waiting for you query to return.
Even if you do use all the columns brought from a "select *...", that's just for now. If in the future you change the table/view layout and add more columns, you'll start bring those in your selects even if you don't need them.
Another point in which a "select *" statement is bad is on view creation. If you create a view using "select *" and later add columns to your table, the view definition and the data returned won't match, and you'll need to recompile your views in order for them to work again.
I know that writing a "select *" is tempting, 'cause I really don't like to manually specify all the fields on my queries, but when your system start to evolve, you'll see that it's worth to spend this extra time/effort in specifying the fields rather than spending much more time and effort removing bugs on your views or optimizing your app.
While explicitly listing columns is good for performance, don't get crazy.
So if you use all the data, try SELECT * for simplicity (imagine having many columns and doing a JOIN... query may get awful). Then - measure. Compare with query with column names listed explicitly.
Don't speculate about performance, measure it!
Explicit listing helps most when you have some column containing big data (like body of a post or article), and don't need it in given query. Then by not returning it in your answer DB server can save time, bandwidth, and disk throughput. Your query result will also be smaller, which is good for any query cache.
You should really be selecting only the fields you need, and only the required number, i.e.
SELECT Field1, Field2 FROM SomeTable WHERE --(constraints)
Outside of the database, dynamic queries run the risk of injection attacks and malformed data. Typically you get round this using stored procedures or parameterised queries. Also (although not really that much of a problem) the server has to generate an execution plan each time a dynamic query is executed.
It is NOT faster to use explicit field names versus *, if and only if, you need to get the data for all fields.
Your client software shouldn't depend on the order of the fields returned, so that's a nonsense too.
And it's possible (though unlikely) that you need to get all fields using * because you don't yet know what fields exist (think very dynamic database structure).
Another disadvantage of using explicit field names is that if there are many of them and they're long then it makes reading the code and/or the query log more difficult.
So the rule should be: if you need all the fields, use *, if you need only a subset, name them explicitly.
The result is too huge. It is slow to generate and send the result from the SQL engine to the client.
The client side, being a generic programming environment, is not and should not be designed to filter and process the results (e.g. the WHERE clause, ORDER clause), as the number of rows can be huge (e.g. tens of millions of rows).
Naming each column you expect to get in your application also ensures your application won't break if someone alters the table, as long as your columns are still present (in any order).
Performance wise I have seen comments that both are equal. but usability aspect there are some +'s and -'s
When you use a (select *) in a query and if some one alter the table and add new fields which do not need for the previous query it is an unnecessary overhead. And what if the newly added field is a blob or an image field??? your query response time is going to be really slow then.
In other hand if you use a (select col1,col2,..) and if the table get altered and added new fields and if those fields are needed in the result set, you always need to edit your select query after table alteration.
But I suggest always to use select col1,col2,... in your queries and alter the query if the table get altered later...
This is an old post, but still valid. For reference, I have a very complicated query consisting of:
12 tables
6 Left joins
9 inner joins
108 total columns on all 12 tables
I only need 54 columns
A 4 column Order By clause
When I execute the query using Select *, it takes an average of 2869ms.
When I execute the query using Select , it takes an average of 1513ms.
Total rows returned is 13,949.
There is no doubt selecting column names means faster performance over Select *
Select is equally efficient (in terms of velocity) if you use * or columns.
The difference is about memory, not velocity. When you select several columns SQL Server must allocate memory space to serve you the query, including all data for all the columns that you've requested, even if you're only using one of them.
What does matter in terms of performance is the excecution plan which in turn depends heavily on your WHERE clause and the number of JOIN, OUTER JOIN, etc ...
For your question just use SELECT *. If you need all the columns there's no performance difference.
It depends on the version of your DB server, but modern versions of SQL can cache the plan either way. I'd say go with whatever is most maintainable with your data access code.
One reason it's better practice to spell out exactly which columns you want is because of possible future changes in the table structure.
If you are reading in data manually using an index based approach to populate a data structure with the results of your query, then in the future when you add/remove a column you will have headaches trying to figure out what went wrong.
As to what is faster, I'll defer to others for their expertise.
As with most problems, it depends on what you want to achieve. If you want to create a db grid that will allow all columns in any table, then "Select *" is the answer. However, if you will only need certain columns and adding or deleting columns from the query is done infrequently, then specify them individually.
It also depends on the amount of data you want to transfer from the server. If one of the columns is a defined as memo, graphic, blob, etc. and you don't need that column, you'd better not use "Select *" or you'll get a whole bunch of data you don't want and your performance could suffer.
To add on to what everyone else has said, if all of your columns that you are selecting are included in an index, your result set will be pulled from the index instead of looking up additional data from SQL.
SELECT * is necessary if one wants to obtain metadata such as the number of columns.
Gonna get slammed for this, but I do a select * because almost all my data is retrived from SQL Server Views that precombine needed values from multiple tables into a single easy to access View.
I do then want all the columns from the view which won't change when new fields are added to underlying tables. This has the added benefit of allowing me to change where data comes from. FieldA in the View may at one time be calculated and then I may change it to be static. Either way the View supplies FieldA to me.
The beauty of this is that it allows my data layer to get datasets. It then passes them to my BL which can then create objects from them. My main app only knows and interacts with the objects. I even allow my objects to self-create when passed a datarow.
Of course, I'm the only developer, so that helps too :)
What everyone above said, plus:
If you're striving for readable maintainable code, doing something like:
SELECT foo, bar FROM widgets;
is instantly readable and shows intent. If you make that call you know what you're getting back. If widgets only has foo and bar columns, then selecting * means you still have to think about what you're getting back, confirm the order is mapped correctly, etc. However, if widgets has more columns but you're only interested in foo and bar, then your code gets messy when you query for a wildcard and then only use some of what's returned.
And remember if you have an inner join by definition you do not need all the columns as the data in the join columns is repeated.
It's not like listing columns in SQl server is hard or even time-consuming. You just drag them over from the object browser (you can get all in one go by dragging from the word columns). To put a permanent performance hit on your system (becasue this can reduce the use of indexes and becasue sending unneeded data over the network is costly) and make it more likely that you will have unexpected problems as the database changes (sometimes columns get added that you do not want the user to see for instance) just to save less than a minute of development time is short-sighted and unprofessional.
Absolutely define the columns you want to SELECT every time. There is no reason not to and the performance improvement is well worth it.
They should never have given the option to "SELECT *"
If you need every column then just use SELECT * but remember that the order could potentially change so when you are consuming the results access them by name and not by index.
I would ignore comments about how * needs to go get the list - chances are parsing and validating named columns is equal to the processing time if not more. Don't prematurely optimize ;-)
What are some of the methods/techniques experienced SQL developers use to determine if a particular SQL query will scale well as load increases, rows in associated tables increase etc.
Some rules that I follow that make the most difference.
Don't use per-row functions in your queries like if, case, coalesce and so on. Work around them by putting data in the database in the format you're going to need it, even if that involves duplicate data.
For example, if you need to lookup surnames fast, store them in the entered form and in their lowercase form, and index the lowercase form. Then you don't have to worry about things like select * from tbl where lowercase(surname) = 'smith';
Yes, I know that breaks 3NF but you can still guarantee data integrity by judicious use of triggers or pre-computed columns. For example, an insert/update trigger on the table can force the lower_surname column to be set to the lowercase version of surname.
This moves the cost of conversion to the insert/update (which happens infrequently) and away from the select (which happens quite a lot more). You basically amortise the cost of conversion.
Make sure that every column used in a where clause is indexed. Not necessarily on its own but at least as the primary part of a composite key.
Always start off in 3NF and only revert if you have performance problems (in production). 3NF is often the easiest to handle and reverting should only be done when absolutely necessary.
Profile, in production (or elsewhere, as long as you have production data and schemas). Database tuning is not a set-and-forget operation unless the data in your tables never changes (very rare). You should be monitoring, and possibly tuning, periodically to avoid the possibility that changing data will bring down performance.
Don't, unless absolutely necessary, allow naked queries to your database. Try to control what queries can be run. Your job as a DBA will be much harder if some manager can come along and just run:
select * from very_big_table order by column_without_index;
on your database.
If managers want to be able to run ad-hoc queries, give them a cloned DBMS (or replica) so that your real users (the ones that need performance) aren't affected.
Don't use union when union all will suffice. If you know that there can be no duplicates between two selects of a union, there's no point letting the DBMS try to remove them.
Similarly, don't use select distinct on a table if you're retrieving all the primary key columns (or all columns in a unique constraint). There is no possibility of duplicates in those cases so, again, you're asking the DBMS to do unnecessary work.
Example: we had a customer with a view using select distinct * on one of their tables. Querying the view took 50 seconds. When we replaced it with a view starting select *, the time came down to sub-second. Needless to say, I got a good bottle of red wine out of that :-)
Try to avoid select * as much as possible. In other words, only get the columns you need. This makes little difference when you're using MySQL on your local PC but, when you have an app in California querying a database in Inner Mongolia, you want to minimise the amount of traffic being sent across the wire as much as possible.
don't make tables wide, keep them narrow as well as the indexes. Make sure that queries are fully covered by indexes and that those queries are SARGable.
Test with a ton of data before going in production, take a look at this: Your testbed has to have the same volume of data as on production in order to simulate normal usage
Pull up the execution plan and look for any of the following:
Table Scan
[Clustered] Index Scan
RID Lookup
Bookmark Lookup
Key Lookup
Nested Loops
Any of those things (in descending order from most to least scalable) mean that the database/query likely won't scale to much larger tables. An ideal query will have mostly index seeks, hash or merge joins, the occasional sort, and other low-impact operations (spools and so on).
The only way to prove that it will scale, as other answers have pointed out, is to test it on data of the desired size. The above is just a rule of thumb.
In addition (and along the same lines) to Robert's suggestion, consider the execution plan. Is it utilizing indexes? Are there any scans or such? Can you simply for the query in any way? For example, Eliminate IN in favor of EXISTS and only join to tables you need to join to.
You don't mention the technology -- keep in mind that different technologies can affect the efficiency of more complex queries.
I strongly recommend reading some reference material on this. This (hyperlink below) is probably a pretty good book to look into. Make sure to look under "Selectivity", among other topics.
SQL Tuning - Dan Tow
I've always preached to my developers that SELECT * is evil and should be avoided like the plague.
Are there any cases where it can be justified?
I'm not talking about COUNT(*) - which most optimizers can figure out.
Edit
I'm talking about production code.
And one great example I saw of this bad practice was a legacy asp application that used select * in a stored procedure, and used ADO to loop through the returned records, but got the columns by index. You can imagine what happened when a new field was added somewhere other than the end of the field list.
I'm quite happy using * in audit triggers.
In that case it can actually prove a benefit because it will ensure that if additional columns are added to the base table it will raise an error so it cannot be forgotten to deal with this in the audit trigger and/or audit table structure.
(Like dotjoe) I am also happy using it in derived tables and column table expressions. Though I habitually do it the other way round.
WITH t
AS (SELECT *,
ROW_NUMBER() OVER (ORDER BY a) AS RN
FROM foo)
SELECT a,
b,
c,
RN
FROM t;
I'm mostly familiar with SQL Server and there at least the optimiser has no problem recognising that only columns a,b,c will be required and the use of * in the inner table expression does not cause any unnecessary overhead retrieving and discarding unneeded columns.
In principle SELECT * ought to be fine in a view as well as it is the final SELECT from the view where it ought to be avoided however in SQL Server this can cause problems as it stores column metadata for views which is not automatically updated when the underlying tables change and the use of * can lead to confusing and incorrect results unless sp_refreshview is run to update this metadata.
There are many scenarios where SELECT * is the optimal solution. Running ad-hoc queries in Management Studio just to get a sense of the data you're working with. Querying tables where you don't know the column names yet because it's the first time you've worked with a new schema. Building disposable quick'n'dirty tools to do a one-time migration or data export.
I'd agree that in "proper" development, you should avoid it - but there's lots of scenarios where "proper" development isn't necessarily the optimum solution to a business problem. Rules and best practices are great, as long as you know when to break them. :)
I'll use it in production when working with CTEs. But, in this case it's not really select *, because I already specified the columns in the CTE. I just don't want to respecify in the final select.
with t as (
select a, b, c from foo
)
select t.* from t;
None that I can think of, if you are talking about live code.
People saying that it makes adding columns easier to develop (so they automatically get returned and can be used without changing the Stored procedure) have no idea about writing optimal code/sql.
I only ever use it when writing ad-hoc queries that will not get reused (finding out the structure of a table, getting some data when I am not sure what the column names are).
I think using select * in an exists clause is appropriate:
select some_field from some_table
where exists
(select * from related_table [join condition...])
Some people like to use select 1 in this case, but it's not elegant, and it doesn't buy any performance improvements (early optimization strikes again).
In production code, I'd tend to agree 100% with you.
However, I think that the * more than justifies its existence when performing ad-hoc queries.
You've gotten a number of answers to your question, but you seem to be dismissing everything that isn't parroting back what you want to hear. Still, here it is for the third (so far) time: sometimes there is no bottleneck. Sometimes performance is way better than fine. Sometimes the tables are in flux, and amending every SELECT query is just one more bit of possible inconsistency to manage. Sometimes you've got to deliver on an impossible schedule and this is the last thing you need to think about.
If you live in bullet time, sure, type in all the column names. But why stop there? Re-write your app in a schema-less dbms. Hell, write your own dbms in assembly. That'd really show 'em.
And remember if you use select * and you have a join at least one field will be sent twice (the join field). This wastes database resources and network resources for no reason.
As a tool I use it to quickly refresh my memory as to what I can possibly get back from a query. As a production level query itself .. no way.
When creating an application that deals with the database, like phpmyadmin, and you are in a page where to display a full table, in that case using SELECT * can be justified, I guess.
About the only thing that I can think of would be when developing a utility or SQL tool application that is being written to run against any database. Even here though, I would tend to query the system tables to get the table structure and then build any necessary query from that.
There was one recent place where my team used SELECT * and I think that it was ok... we have a database that exists as a facade against another database (call it DB_Data), so it is primarily made up of views against the tables in the other database. When we generate the views we actually generate the column lists, but there is one set of views in the DB_Data database that are automatically generated as rows are added to a generic look-up table (this design was in place before I got here). We wrote a DDL trigger so that when a view is created in DB_Data by this process then another view is automatically created in the facade. Since the view is always generated to exactly match the view in DB_Data and is always refreshed and kept in sync, we just used SELECT * for simplicity.
I wouldn't be surprised if most developers went their entire career without having a legitimate use for SELECT * in production code though.
I've used select * to query tables optimized for reading (denormalized, flat data). Very advantageous since the purpose of the tables were simply to support various views in the application.
How else do the developers of phpmyadmin ensure they are displaying all the fields of your DB tables?
It is conceivable you'd want to design your DB and application so that you can add a column to a table without needing to rewrite your application. If your application at least checks column names it can safely use SELECT * and treat additional columns with some appropriate default action. Sure the app could consult system catalogs (or app-specific catalogs) for column information, but in some circumstances SELECT * is syntactic sugar for doing that.
There are obvious risks to this, however, and adding the required logic to the app to make it reliable could well simply mean replicating the DB's query checks in a less suitable medium. I am not going to speculate on how the costs and benefits trade off in real life.
In practice, I stick to SELECT * for 3 cases (some mentioned in other answers:
As an ad-hoc query, entered in a SQL GUI or command line.
As the contents of an EXISTS predicate.
In an application that dealt with generic tables without needing to know what they mean (e.g. a dumper, or differ).
Yes, but only in situations where the intention is to actually get all the columns from a table not because you want all the columns that a table currently has.
For example, in one system that I worked on we had UDFs (User Defined Fields) where the user could pick the fields they wanted on the report, the order as well as filtering. When building a result set it made more sense to simply "select *" from the temporary tables that I was building instead of having to keep track of which columns were active.
I have several times needed to display data from a table whose column names were unknown. So I did SELECT * and got the column names at run time.
I was handed a legacy app where a table had 200 columns and a view had 300. The risk exposure from SELECT * would have been no worse than from listing all 300 columns explicitly.
Depends on the context of the production software.
If you are writing a simple data access layer for a table management tool where the user will be selecting tables and viewing results in a grid, then it would seem *SELECT ** is fine.
In other words, if you choose to handle "selection of fields" through some other means (as in automatic or user-specified filters after retrieving the resultset) then it seems just fine.
If on the other hand we are talking about some sort of enterprise software with business rules, a defined schema, etc. ... then I agree that *SELECT ** is a bad idea.
EDIT: Oh and when the source table is a stored procedure for a trigger or view, "*SELECT **" should be fine because you're managing the resultset through other means (the view's definition or the stored proc's resultset).
Select * in production code is justifiable any time that:
it isn't a performance bottleneck
development time is critical
Why would I want the overhead of going back and having to worry about changing the relevant stored procedures, every time I add a field to the table?
Why would I even want to have to think about whether or not I've selected the right fields, when the vast majority of the time I want most of them anyway, and the vast majority of the few times I don't, something else is the bottleneck?
If I have a specific performance issue then I'll go back and fix that. Otherwise in my environment, it's just premature (and expensive) optimisation that I can do without.
Edit.. following the discussion, I guess I'd add to this:
... and where people haven't done other undesirable things like tried to access columns(i), which could break in other situations anyway :)
I know I'm very late to the party but I'll chip in that I use select * whenever I know that I'll always want all columns regardless of the column names. This may be a rather fringe case but in data warehousing, I might want to stage an entire table from a 3rd party app. My standard process for this is to drop the staging table and run
select *
into staging.aTable
from remotedb.dbo.aTable
Yes, if the schema on the remote table changes, downstream dependencies may throw errors but that's going to happen regardless.
If you want to find all the columns and want order, you can do the following (at least if you use MySQL):
SHOW COLUMNS FROM mytable FROM mydb; (1)
You can see every relevant information about all your fields. You can prevent problems with types and you can know for sure all the column names. This command is very quick, because you just ask for the structure of the table. From the results you will select all the name and will build a string like this:
"select " + fieldNames[0] + ", fieldNames[1]" + ", fieldNames[2] from mytable". (2)
If you don't want to run two separate MySQL commands because a MySQL command is expensive, you can include (1) and (2) into a stored procedure which will have the results as an OUT parameter, that way you will just call a stored procedure and every command and data generation will happen at the database server.
I am working on someone else's PHP code and seeing this pattern over and over:
(pseudocode)
result = SELECT blah1, blah2, foreign_key FROM foo WHERE key=bar
if foreign_key > 0
other_result = SELECT something FROM foo2 WHERE key=foreign_key
end
The code needs to branch if there is no related row in the other table, but couldn't this be done better by doing a LEFT JOIN in a single SELECT statement? Am I missing some performance benefit? Portability issue? Or am I just nitpicking?
This is definitely wrong. You are going over the wire a second time for no reason. DBs are very fast at their problem space. Joining tables is one of those and you'll see more of a performance degradation from the second query then the join. Unless your tablespace is hundreds of millions of records, this is not a good idea.
There is not enough information to really answer the question. I've worked on applications where decreasing the query count for one reason and increasing the query count for another reason both gave performance improvements. In the same application!
For certain combinations of table size, database configuration and how often the foreign table would be queried, doing the two queries can be much faster than a LEFT JOIN. But experience and testing is the only thing that will tell you that. MySQL with moderately large tables seems to be susceptable to this, IME. Performing three queries on one table can often be much faster than one query JOINing the three. I've seen speedups of an order of magnitude.
I'm with you - a single SQL would be better
There's a danger of treating your SQL DBMS as if it was a ISAM file system, selecting from a single table at a time. It might be cleaner to use a single SELECT with the outer join. On the other hand, detecting null in the application code and deciding what to do based on null vs non-null is also not completely clean.
One advantage of a single statement - you have fewer round trips to the server - especially if the SQL is prepared dynamically each time the other result is needed.
On average, then, a single SELECT statement is better. It gives the optimizer something to do and saves it getting too bored as well.
It seems to me that what you're saying is fairly valid - why fire off two calls to the database when one will do - unless both records are needed independently as objects(?)
Of course while it might not be as simple code wise to pull it all back in one call from the database and separate out the fields into the two separate objects, it does mean that you're only dependent on the database for one call rather than two...
This would be nicer to read as a query:
Select a.blah1, a.blah2, b.something From foo a Left Join foo2 b On a.foreign_key = b.key Where a.Key = bar;
And this way you can check you got a result in one go and have the database do all the heavy lifting in one query rather than two...
Yeah, I think it seems like what you're saying is correct.
The most likely explanation is that the developer simply doesn't know how outer joins work. This is very common, even among developers who are quite experienced in their own specialty.
There's also a widespread myth that "queries with joins are slow." So many developers blindly avoid joins at all costs, even to the extreme of running multiple queries where one would be better.
The myth of avoiding joins is like saying we should avoid writing loops in our application code, because running a line of code multiple times is obviously slower than running it once. To say nothing of the "overhead" of ++i and testing i<20 during every iteration!
You are completely correct that the single query is the way to go. To add some value to the other answers offered let me add this axiom: "Use the right tool for the job, the Database server should handle the querying work, the code should handle the procedural work."
The key idea behind this concept is that the compiler/query optimizers can do a better job if they know the entire problem domain instead of half of it.
Considering that in one database hit you have all the data you need having one single SQL statement would be better performance 99% of the time. Not sure if the connections is being creating dynamically in this case or not but if so doing so is expensive. Even if the process if reusing existing connections the DBMS is not getting optimize the queries be best way and not really making use of the relationships.
The only way I could ever see doing the calls like this for performance reasons is if the data being retrieved by the foreign key is a large amount and it is only needed in some cases. But in the sample you describe it just grabs it if it exists so this is not the case and therefore not gaining any performance.
The only "gotcha" to all of this is if the result set to work with contains a lot of joins, or even nested joins.
I've had two or three instances now where the original query I was inheriting consisted of a single query that had so a lot of joins in it and it would take the SQL a good minute to prepare the statement.
I went back into the procedure, leveraged some table variables (or temporary tables) and broke the query down into a lot of the smaller single select type statements and constructed the final result set in this manner.
This update dramatically fixed the response time, down to a few seconds, because it was easier to do a lot of simple "one shots" to retrieve the necessary data.
I'm not trying to object for objections sake here, but just to point out that the code may have been broken down to such a granular level to address a similar issue.
A single SQL query would lead in more performance as the SQL server (Which sometimes doesn't share the same location) just needs to handle one request, if you would use multiple SQL queries then you introduce a lot of overhead:
Executing more CPU instructions,
sending a second query to the server,
create a second thread on the server,
execute possible more CPU instructions
on the sever, destroy a second thread
on the server, send the second results
back.
There might be exceptional cases where the performance could be better, but for simple things you can't reach better performance by doing a bit more work.
Doing a simple two table join is usually the best way to go after this problem domain, however depending on the state of the tables and indexing, there are certain cases where it may be better to do the two select statements, but typically I haven't run into this problem until I started approaching 3-5 joined tables, not just 2.
Just make sure you have covering indexes on both tables to ensure you aren't scanning the disk for all records, that is the biggest performance hit a database gets (in my limited experience)
You should always try to minimize the number of query to the database when you can. Your example is perfect for only 1 query. This way you will be able later to cache more easily or to handle more request in same time because instead of always using 2-3 query that require a connexion, you will have only 1 each time.
There are many cases that will require different solutions and it isn't possible to explain all together.
Join scans both the tables and loops to match the first table record in second table. Simple select query will work faster in many cases as It only take cares for the primary/unique key(if exists) to search the data internally.