How many records should there be before I consider indexing my sql tables?
There's no good reason to forego obvious indexes (FKs, etc.) when you're creating the table. It will never noticeably affect performance to have unnecessary indexes on tiny tables, and it's good to take a first cut when your mind is into schema design. Also, some indexes serve to prevent duplicates, which can be useful regardless of table size.
I guess the proper answer to your question is that the number of records in the table should have nothing to do with when to create indexes.
I would create the index entries when I create my table. If you decide to create indices after the table has grown to 100, 1000, 100000 entries it can just take alot of time and perhaps make your database unavailable while you are doing it.
Think about the table first, create the indices you think you'll need, and then move on.
In some cases you will discover that you should have indexed a column, if thats the case, fix it when you discover it.
Creating an index on a searched field is not a pre-optimization, its just what should be done.
When the query time is unacceptable. Better yet, create a few indexes now that are likely to be useful, and run an EXPLAIN or EXPLAIN ANALYZE on your queries once your database is populated by representative data. If the indexes aren't helping, drop them. If there are slow queries that could benefit from more or different indexes, change the indexes.
You are not going to be locked in to an initial choice of indexes. Experiment, and make sure you measure performance!
In general I agree with the previous advice.
Always declare the referential integrity for the tables (Primary Key, Foreign Keys), column constraints (not null, check). Saves you from nightmares when apps put bad data into the tables (even in development).
I'd consider adding indexes for the common access columns (columns in your where clauses which are used in =, <> tests), as well.
Most of the modern RDBMS implementations are quite good at keeping you indexes up to date, without hitting your performance. So, the cost of having indexes is minimal.
Also, most RDBMS's have query plan evaluators which look at the relative costs going to the data rows via the index, or using some sort of table scan. So, again the performance hits are minimal.
Two.
I'm serious. If there are two rows now, and there will always be two rows, the cost of indexing is almost zero. It's quicker to index than to ponder whether you should. It won't take the optimizer very long to figure out that scanning the table is quicker than using the index.
If there are two rows now, but there will be 200,000 in the near future, the cost of not indexing could become prohibitively high. The right time to consider indexing is now.
Having said this, remember that you get an index automatically when you declare a primary key. Creating a table with no primary key is asking for trouble in most cases. So the only time you really need to consider indexing is when you want an index other than the index on the primary key. You need to know the traffic, and the anticipated volume to make this call. If you get it wrong, you'll know, and you can reverse the decision.
I once saw a reference table that had been created with no index when it contained 20 rows. Due to a business change, this table had grown to about 900 rows, but the person who should have noticed the absence of an index didn't. The time to insert a new order had grown from about 10 seconds to 15 minutes.
As a matter of routine I perform the following on read heavy tables:
Create indexes on common join fields such as Foreign Keys when I create the table.
Check the query plan for Views or Stored Procedures and add indexes wherever a table scan is indicated.
Check the query plan for queries by my application and add indexes wherever a table scan is indicated. (and often try to make them into Stored Procedures)
On write heavy tables (like activity logs) I avoid indexes unless they are absolutely necessary. I also tend to archive such data into indexed tables at regular intervals.
It depends.
How much data is in the table? How often is data inserted? A lot of indexes can slow down insertion time. Do you always query all the rows of the table? In this case indexes probably won't help much.
Those aren't common usages though. In most cases, you know you're going to be querying a subset of data. ON what fields? Are there common fields that are always joined on? Look at query plans for common or typical queries, it will generally show you where it's spending all of its time.
If there's a unique constraint on the table (and there should be at least one), then that will usually be enforced by a unique index.
Otherwise, you add indexes when the query performance is bad and adding the index will demonstrably improve the performance. There are books on the subject of how to create good sets of indexes on tables, including Relational Database Index Design and the Optimizers. It will give you a lot of ideas and the reasons why they are good.
See also:
No indexes on small tables
When to create a new SQL Server index
Best Practices and Anti-Patterns in Creating Indexes
and, no doubt, a host of others.
Related
Adding indexes is often suggested here as a remedy for performance problems.
(I'm talking about reading & querying ONLY, we all know indexes can make writing slower).
I have tried this remedy many times, over many years, both on DB2 and MSSQL, and the result were invariably disappointing.
My finding has been that no matter how 'obvious' it was that an index would make things better, it turned out that the query optimiser was smarter, and my cleverly-chosen index almost always made things worse.
I should point out that my experiences relate mostly to small tables (<100'000 rows).
Can anyone provide some down-to-earth guidelines on choices for indexing?
The correct answer would be a list of recommendations something like:
Never/always index a table with less than/more than NNNN records
Never/always consider indexes on multi-field keys
Never/always use clustered indexes
Never/always use more than NNN indexes on a single table
Never/always add an index when [some magic condition I'm dying to learn about]
Ideally, the answer will give some instructive examples.
Indexes are kind of like chemotherapy...too much and it kills you...too little and you die...do it the wrong way and you die. You gotta know just how much, how often, and what kind to make it not kill you.
Your hardware, platform, environment, load all play a role. So to answer your questions..
Yes, possibly sometimes.
As a rule of thumb, primary keys and foreign keys need to be indexed. Usually primary key are indexed just by defining them as such, but FKs are not in every database (they definitely are not in SQL Server, I can't really speak for other dbs). You will be using these in joins, so it is generally critical to performance to define these.
Now if you have fields you often use in where clauses, they can benefit from indexes as well providing several things:
First the field must have a range of
values. A bit field or a field with
only 2 or 3 values will almost never
use an index.
Second the queries you write must be sargable. That is they must be designed to use indexes. I suspect if you never get performance improvements from what look like likely candidates for indexes, then you probably have queries that are not sargable. For instance take "WHERE Name like '%Smith'" as a where clause. Without knowing the first characters, the optimizer can't use the index.
Small tables rarely benefit much from indexes. If the optimizer can hold the whole thing in memory, then it is often faster to do so. If you were working with multimillion record tables, you would see that indexes are critical.
Indexing can be very complex and if you are interested in the subject, I suggest you get a good book on performance tuning your particular database and read in depth about them.
An index that's never used is a waste of disk space, as well as adding to the insert/update/delete time. It's probably best to define the clustering index first, then define
additional indexes as you find yourself writing WHERE clauses.
One common index mistake I see is people wondering why a select on col2 (or col3) takes so long when the index is defined as col1 ASC, col2 ASC, col3 ASC. When you have a multiple column index, your WHERE clause must use the first column in the index, or the first and second column in the index, and so forth.
If you need to access the data by col2, then you need an additional index that's defined as col2 ASC.
With small domain tables, it's sometimes faster to do a table scan than it is to read rows from the table using an index. This depends on the speed of your database machine and the speed of the network.
You need indexes. Only with indexes you can access data fast enough.
To make it as short as possible:
add indexes for columns you are frequently filtering (or grouping) for. (eg. a state or name)
like and sql functions could make the DBMS not use indexes.
add indexes only on columns which have many different values (eg. no boolean fields)
It is common to add indexes to foreign keys, but it is not always needed.
don't add indexes in very short tables
never add indexes when you don't know how they should enhance performance.
Finally: look into execution plans to decide how to optimize queries.
You'll add indexes just for a single, critical query. In this case, you'll add exactly the indexes that are needed in the query in question (multi-column indexes).
Basically when DB is collecting data and it's alive indexes have to go and evolve with that flow. There maybe really good index on table but after growing beyond of XXX records the same index in the same table is useless and in that case it should be refactored.
To have optimized and fast DB the only way is to monitor it all the time and refactor it over the time as records come in.
Real life example i got some time ago was super fast query restricted by some time range (created_at between A and B) and super slow query where time range was different. Same query, same database, same application and only one difference on time range.
Always use clustered indexes.
In fact you can't help but using them. The data in a table will be laid out on disk in some particular order anyway, it can't be save as a pile or something. You have the chance of specifying how exactly this data will be laid out. Why burn it?
When you have a table which gets new records appended and you observe that some value in those records always grow (like StackOverflow question number), make a clustered index out of it. Then the new data will not be inserted in the middle but will basically be appended to a file on disk which is a relatively cheap operation.
If a table is expected to be the target of a join then it is best to have a clustered index on that table so that the joins can be performed sequentially through the data pages. The columns in the clustered index will (on some DB systems) be included in all of the other indexes on that table, since those are the values that the indexes will use to reference the table data. To keep the other indexes from getting too large, the columns in the clustered index should be as narrow as possible, so it is best to use only numeric—rather than character—data types in the clustered index. In general, fewer columns are better than more columns, but notice that three int columns (12 bytes per row) are much better than one nvarchar(32) column (potentially 64 bytes per row).
If the clustered index is narrow, then a few additional indexes should not negatively impact performance very much even on very large tables.
Seems you are confusing two concepts here.
Adding indices *generally can only make a read query faster, very very rarely (almost never) slower. Adding an index never forces the query optimizer to use it. It will only use it if it thinks it can benefit from it, and it is generally very smart about those decisions.
For inserts/updates, of course, every index hurts performance a bit more... But at the other end of the spectrum, for, say a read only database, (like a USPS address database which is distributed monthly), in operational use there would ne no inserts/updates, so the only negative impact of additional indices is the disk space they take up.
This is entirely different that specifying that the query optimizer USE an index, in effect overriding what it would do on it's own... That can potentially make a query slower.
EDIT: Edited to eliminate opportunity for misinterpretation by overly literal readers.
I've searched a bit and didn't see any similar question, so here goes.
How do you know when to put an index in a table? How do you decide which columns to include in the index? When should a clustered index be used?
Can an index ever slow down the performance of select statements? How many indexes is too many and how big of a table do you need for it to benefit from an index?
EDIT:
What about column data types? Is it ok to have an index on a varchar or datetime?
Well, the first question is easy:
When should a clustered index be used?
Always. Period. Except for a very few, rare, edge cases. A clustered index makes a table faster, for every operation. YES! It does. See Kim Tripp's excellent The Clustered Index Debate continues for background info. She also mentions her main criteria for a clustered index:
narrow
static (never changes)
unique
if ever possible: ever increasing
INT IDENTITY fulfills this perfectly - GUID's do not. See GUID's as Primary Key for extensive background info.
Why narrow? Because the clustering key is added to each and every index page of each and every non-clustered index on the same table (in order to be able to actually look up the data row, if needed). You don't want to have VARCHAR(200) in your clustering key....
Why unique?? See above - the clustering key is the item and mechanism that SQL Server uses to uniquely find a data row. It has to be unique. If you pick a non-unique clustering key, SQL Server itself will add a 4-byte uniqueifier to your keys. Be careful of that!
Next: non-clustered indices. Basically there's one rule: any foreign key in a child table referencing another table should be indexed, it'll speed up JOINs and other operations.
Furthermore, any queries that have WHERE clauses are a good candidate - pick those first which are executed a lot. Put indices on columns that show up in WHERE clauses, in ORDER BY statements.
Next: measure your system, check the DMV's (dynamic management views) for hints about unused or missing indices, and tweak your system over and over again. It's an ongoing process, you'll never be done! See here for info on those two DMV's (missing and unused indices).
Another word of warning: with a truckload of indices, you can make any SELECT query go really really fast. But at the same time, INSERTs, UPDATEs and DELETEs which have to update all the indices involved might suffer. If you only ever SELECT - go nuts! Otherwise, it's a fine and delicate balancing act. You can always tweak a single query beyond belief - but the rest of your system might suffer in doing so. Don't over-index your database! Put a few good indices in place, check and observe how the system behaves, and then maybe add another one or two, and again: observe how the total system performance is affected by that.
Rule of thumb is primary key (implied and defaults to clustered) and each foreign key column
There is more but you could do worse than using SQL Server's missing index DMVs
An index may slow down a SELECT if the optimiser makes a bad choice, and it is possible to have too many. Too many will slow writes but it's also possible to overlap indexes
Answering the ones I can I would say that every table, no matter how small, will always benefit from at least one index as there has to be at least one way in which you are interested in looking up the data; otherwise why store it?
A general rule for adding indexes would be if you need to find data in the table using a particular field, or set of fields. This leads on to how many indexes are too many, generally the more indexes you have the slower inserts and updates will be as they also have to modify the indexes but it all depends on how you use your data. If you need fast inserts then don't use too many. In reporting "read only" type data stores you can have a number of them to make all your lookups faster.
Unfortunately there is no one rule to guide you on the number or type of indexes to use, although the query optimiser of your chosen DB can give hints based on the queries you are executing.
As to clustered indexes they are the Ace card you only get to use once, so choose carefully. It's worth calculating the selectivity of the field you are thinking of putting it on as it can be wasted to put it on something like a boolean field (contrived example) as the selectivity of the data is very low.
This is really a very involved question, though a good starting place would be to index any column that you will filter results on. ie. If you often break products into groups by sale price, index the sale_price column of the products table to improve scan times for that query, etc.
If you are querying based on the value in a column, you probably want to index that column.
i.e.
SELECT a,b,c FROM MyTable WHERE x = 1
You would want an index on X.
Generally, I add indexes for columns which are frequently queried, and I add compound indexes when I'm querying on more than one column.
Indexes won't hurt the performance of a SELECT, but they may slow down INSERTS (or UPDATES) if you have too many indexes columns per table.
As a rule of thumb - start off by adding indexes when you find yourself saying WHERE a = 123 (in this case, an index for "a").
You should use an index on columns that you use for selection and ordering - i.e. the WHERE and ORDER BY clauses.
Indexes can slow down select statements if there are many of them and you are using WHERE and ORDER BY on columns that have not been indexed.
As for size of table - several thousands rows and upwards would start showing real benefits to index usage.
Having said that, there are automated tools to do this, and SQL server has an Database Tuning Advisor that will help with this.
I have an MS SQL server application where I have defined my relationships and primary keys.
However do I need to further define indexes on relationship fields which are sometimes not used in joins and just as part of a where clause?
I am working on the assumption that defining a relationship creates an index, which the sql engine can reuse.
Some very thick books have been written on this subject!
Here are some ruiles of thumb:-
Dont bother indexing (apart from PK) any table with < 1000 rows.
Otherwise index all your FKs.
Examine your SQL and look for the where clauses that will most reduce your result sets and index that columun.
eg. given:
SELECT OWNER FROM CARS WHERE COLOUR = 'RED' AND MANUFACTURER = "BMW" AND ECAP = "2.0";
You may have 5000 red cars out of 20,000 so indexing this wont help much.
However you may only have 100 BMWs so indexing MANUFACURER will immediatly reduce you result set to 100 and you can eliminate the the blue and white cars by simply scanning through the hundred rows.
Generally the dbms will pick one or two of the indexes available based on cardinality so it pays to second guess and define only those indexes that are likely to be used.
No indexes will be automatically created on foreign keys constraint. But unique and primary key constraints will create theirs.
Creating indexes on the queries you use, be it on joins or on the WHERE clause is the way to go.
Like everything in the programming world, it depends. You obviously want to create indexes and relationships to preserve normalization and speed up database lookups. But you also want to balance that by not having too many indexes that it will take SQL Server more time to build every index. Also the more indexes you have the more fragmentation that can occur in your database.
So what I do is put in the obvious indexes and relationships and then optimize after the application is build on the possible slow queries.
Defining a relationship does not create the index.
Usually in places where you have a where clause against some field you want an index but be careful not to just throw indexes out all over the place because they can and do have an effect on insert/update performance.
I would start by making sure that every PK and FK has an index.
Further to that, I have found that using the Index Tuning Wizard in SSMS provides excellent recommendations when you feed it the right information.
Database Considerations
When you design an index, consider the following database guidelines:
Large numbers of indexes on a table affect the performance of INSERT, UPDATE, DELETE, and MERGE statements because all indexes must be adjusted appropriately as data in the table changes.
Avoid over-indexing heavily updated tables and keep indexes narrow,
that is, with as few columns as possible.
Use many indexes to improve query performance on tables with low
update requirements, but large volumes of data. Large numbers of
indexes can help the performance of queries that do not modify data,
such as SELECT statements, because the query optimizer has more
indexes to choose from to determine the fastest access method.
Indexing small tables may not be optimal because it can take the
query optimizer longer to traverse the index searching for data than
to perform a simple table scan. Therefore, indexes on small tables
might never be used, but must still be maintained as data in the
table changes.
Indexes on views can provide significant performance gains when the
view contains aggregations, table joins, or a combination of
aggregations and joins. The view does not have to be explicitly
referenced in the query for the query optimizer to use it.
--Stay_Safe--
Indexes aren't very expensive, and speed up queries more than you realize. I would recommend adding indexes to all key and non-key fields that are often used in queries. You can even use the execution plan to recommend additional indexes that would speed up your queries.
The only point where indexes aren't in your favour is when you're doing large amounts of data inserts. Each insert requires each index in a table to be updated along with the table's data.
You can opt to wait until the application is running and you have some known queries against the database that you want to improve, or you could do it now, if you have a good idea.
"We should forget about small efficiencies, say about 97% of the time: premature optimization is the root of all evil." (Donald Knuth). My SQL tables are unlikely to contain more than a few thousand rows each (and those are the big ones!). SQL Server Database Engine Tuning Advisor dismisses the amount of data as irrelevant. So I shouldn't even think about putting explicit indexes on these tables. Correct?
The value of indexes is in speeding reads. For instance, if you are doing lots of SELECTs based on a range of dates in a date column, it makes sense to put an index on that column. And of course, generally you add indexes on any column you're going to be JOINing on with any significant frequency. The efficiency gain is also related to the ratio of the size of your typical recordsets to the number of records (i.e. grabbing 20/2000 records benefits more from indexing than grabbing 90/100 records). A lookup on an unindexed column is essentially a linear search.
The cost of indexes comes on writes, because every INSERT also requires an internal insert to each column index.
So, the answer depends entirely on your application -- if it's something like a dynamic website where the number of reads can be 100x or 1000x the writes, and you're doing frequent, disparate lookups based on data columns, indexing may well be beneficial. But if writes greatly outnumber reads, then your tuning should focus on speeding those queries.
It takes very little time to identify and benchmark a handful of your app's most frequent operations both with and without indexes on the JOIN/WHERE columns, I suggest you do that. It's also smart to monitor your production app and identify the most expensive, and most frequent queries, and focus your optimization efforts on the intersection of those two sets of queries (which could mean indexes or something totally different, like allocating more or less memory for query or join caches).
Knuth's wise words are not applicable to the creation (or not) of indexes, since by adding indexes you are not optimising anything directly: you are providing an index that the DBMSs optimiser may use to optimise some queries. In fact, you could better argue that deciding not to index a small table is premature optimisation, as by doing so you restrict the DBMS optimiser's options!
Different DBMSs will have different guidelines for choosing whether or not to index columns based on various factors including table size, and it is these that should be considered.
What is an example of premature optimisation in databases: "denormalising for performance" before any benchmarking has indicated that the normalised database actually has any performance issues.
Primary key columns will be indexed for the unique constraint. I would still index all foreign key columns. The optimizer can choose to ignore your index if it is irrelevant.
If you only have a little bit of data then the extra cost for insert/update should not be significant either.
Absolutely incorrect. 100% incorrect. Don't put a million pointless indexes, but you do want a Primary Key (in most cases), and you do want it CLUSTERED correctly.
Here's why:
SELECT * FROM MySmallTable <-- No worries... Index won't help
SELECT
*
FROM
MyBigTable INNER JOIN MySmallTable ON... <-- Ahh, now I'm glad I have my index.
Here's a good rule to go by.
"Since I have a TABLE, I'm likely going to want to query it at some time... If I'm going to query it, I'm likely going to do so in a consistent way..." <-- That's how you should index the table.
EDIT: I'm adding this line: If you have a concrete example in mind, I'll show you how to index it, and how much of a savings you'll get from doing so. Please supply a table, and an example of how you plan in using that table.
I suggest that you follow the usual rules about indexing, which approximately means "create indexes on those columns that you use in your queries".
This might sound unnecessary with such a small database. As others have already said: as long as your database stays as small as you have described, the queries will be fast enough anyway, and the indexes aren't really needed. They can even slow down insertions and updates, but unless you have very specific requirements there, it doesn't matter with such a small database.
But, if the database grows (which databases sometimes have a tendency to do) you don't have to remember to add indexes to that old database that you've probably forgotten about by then. Maybe it has even been installed at one your customers, and you can't modify it!
I guess what I'm saying is this: indexes should be such a natural part of your database design, that it is the lack of indexes that is the optimization, premature or not.
It depends. Is the table a reference table?
There are tables of a thousand rows where the absence of an index, and the resulting table scans can make the difference between a fairly simple operation delaying the user by 5 minutes instead of 5 seconds. I have seen exactly this problem, using a DBMS other than SQL Server.
Generally, if the table is a reference table, updates on it will be relatively rare. This means that the performance hit for updating the index will also be relatively rare. If the optimizer passes over the index, the performance hit on the optimizer will be negligible. The space needed to store the index will also be negligible.
If you declare a primary key, you should get an automatic index on that key. That automatic index will almost always do you enough good to justify its cost. Leave it in there. If you create a reference table without a primary key, there are other problems in your design methodology.
If you do frequent searches or frequent joins on some set of columns other than the primary key, an additional index might pay for itself. Don't fix that problem unless it is a problem.
Here's the general rule of thumb: go with the default behavior of the DBMS, unless you find a reason not to. Anything else is a premature preoccupation with optimization on your part.
If the rows have narrow width, and a few thousand rows fit on say 10-20 8K pages, it is unlikely that the SQL optimiser would elect to use an index even if you create one.
Put indexes ONLY if you have to :)
There are times when putting indexes can actually hurt performance, depending on what the table is used for...
So, in other words, you would think about putting indexes on tables when it is necessary as determined by profiling the application.
Indexes are often created implicitly when using UNIQUE constraints. I wouldn't try to avoid their use in that case!
As a general rule of thumb, it's good to avoid smaller indexes as they typically won't be used.
But sometimes they can provide a huge boost as I outlined here.
I guess there is an auto indexing on the primary key of the table which should be sufficient when querying on a table with less data.
So, yes explicit indexes can be avoided in case there is a small data set to be worked upon.
Even if you have an index, SQL Server might not even use it, depending on the statistics for that table. And if you plan to put in an index for a report that will run at most a couple times a year, bear in mind that the INSERT/UPDATE penalties for adding the index will be in effect ALL THE TIME. Before adding an index, ask yourself if it is worth the performance penalty.
You have to understand that based upon the query two lookups may be done, one into the index to get the pointer to the row, the next to the row itself. If the data that is being queried is in the index columns that extra step may not be necessary.
It is entirely possible that double dipping for data may be slower even if the optimizer goes after the index. Whether or not we care is up to application profiling and eventual explain plans.
I have a table with many millions of rows. I need to find all the rows with a specific column value. That column is not in an index, so a table scan results.
But would it be quicker to add an index with the column at the head (prime key following), do the query, then drop the index?
I can't add an index permanently as the user is nominating what column they're looking for.
Two questions to think about:
How many columns could be nominated for the query?
Does the data change frequently? A lot of it?
If you have a small number of candidate columns, and the data doesn't change a lot, then you might want to consider adding a permanent index on any or even all candidate column.
"Blasphemy!", I hear. Most sources tell you to "never" index every column of a table, but that advised is rooted on the generic assumption that tables are modified frequently.
You will pay a price in additional storage, as well as a performance hit when the data changes.
How small is small and how much is a lot, and is the tradeoff worth it?
There is no way to tell a priory because "too slow" is usually a subjective measurement.
You will have to try it, measure the size of your indexes and then the effect they have in the searches. You will have to balance the costs against the increase in satisfaction of your customers.
[Added] Oh, one more thing: temporary indexes are not only physically slower than a table scan, but they would destroy your concurrency. Re-indexing a table usually (always?) requires a full table lock, so in effect only one user search could be done at a time.
Good luck.
I'm no DBA, but I would guess that building the index would require scanning the table anyway.
Unless there are going to be multiple queries on that column, I would recommend not creating the index.
Best to check the explain plans/execution times for both ways, though!
As everyone else has said, it most certainly would not be faster to add an index than it would be to do a full scan of that column.
However, I would suggest tracking the query pattern and find out which column(s) are searched for the most, and add indexes at least for them. You may find out that 3-4 indexes speeds up 90% of your queries.
Adding an index requires a table scan, so if you can't add a permanent index it sounds like a single scan will be (slightly) faster.
No, that would not be quicker. What would be quicker is to just add the index and leave it there!
Of course, it may not be practical to index every column, but then again it may. How is data added to the table?
It wouldn't be. Creating an index is more complex than simply scanning the column, even if the computational complexity is the same.
That said - how many columns do you have? Are you sure you can't just create an index for each of them if the query time for a single find is too long?
It depends on the complexity of your query. If you're retrieving the data once, then doing a table scan is faster. However, if you're going back to the table more than once for related information in the same query, then the index is faster.
Another related strategy is to do the table scan, and put all the data in a temporary table. Then index THAT and then you can do all your subsequent selects, groupings, and as many other queries on the subset of indexed data. The benefit being that looking up related information in related tables using the temp table is MUCH faster.
However, space is cheap these days, so you'd probably best be served by examining how your users actually USE your system and adding indexes on those frequent columns. I have yet to see users use ALL the search parameters ALL the time.
Your solution will not scale unless you add a permanent index to each column, with all of the columns that are returned in the query in the list of included columns (a covering index). These indexes will be very large, and inserts and updates to that table will be a bit slower, but you don't have much of a choice if you are allowing a user to arbitrarily select a search column.
How many columns are there? How often does the data get updated? How fast do inserts and updates need to run? There are trade-offs involved, depending on the answers to those questions. Do plenty of experimentation and testing so you know for sure how things will perform.
But to your original question, adding and dropping an index for the purpose of a single query is only beneficial if you do more than one select during the query (for example, the select is in a sub-query that gets run for each row returned).