I wish to analyze the queries executed on certain redshift warehouse (not mine).
In order to do so I'm using a query with a join on stl_querytext and stl_query.
My question is how come I'm also getting illegal queries (I.E queries with wrong sql syntax)?
When I've tried it in my local redshift I haven't seen those. Also, couldn't find relevant documentation.
Is this a configuration issue? And in case I'm supposed to those queries is there a way to know those are illegal ones?
Thanks,
Nir.
So stl_querytext breaks long queries into parts identified by sequence number. I hope you are reconstructing the parts into the original query as a first step. This can be done with listagg() function as long as the resulting query doesn't over the max tex field (about 320 parts).
Now this is not enough to get valid SQL back in all cases because you need to treat combining the parts differently depending if the section of the query is inside or outside a text string in the query. (Is white space needed between parts or not)
I've done this exact process a bunch so this is doable. I don't have a perfect process on the whitespace question, I get close. Maybe others know the expression to get an exact recreation of the query from stl_querytext.
In Sql Server, I have a table containing 46 million rows.
In "Title" column of table, I want make search. The word may be at any index of field value.
For example:
Value in table: BROTHERS COMPANY
Search string: ROTHER
I want this search to match the given record. This is exactly what LIKE '%ROTHER%' do. However, LIKE '%%' usage should not be used on large tables because of performance issues. How can I achieve it?
Though I don't know your requirements, your best approach may be to challenge them. Middle-of-the-string searches are usually not very practical. If you can get your users to perform prefix searches (broth%) then you can easily use Full Text's wildcard search (CONTAINS(*, '"broth*"')). Full Text can also handle suffix searches (%rothers) with a little extra work.
But when it comes to middle-of-the-string searches with SQL Server, you're stuck using LIKE. However you may be able to improve performance of LIKE by using a binary collation as explained in this article. (I hate to post a link without including its content but it is way too long of an article to post here and I don't understand the approach enough to sum it up.)
If that doesn't help and if middle-of-the-string searches are that important of a requirement then you should consider using a different search solution like Lucene.
Add Full-Text index if you want.
You can search the table using CONTAINS:
SELECT *
FROM YourTable
WHERE CONTAINS(TableColumnName, 'SearchItem')
Still pretty new to Rails and hoping to develop a function on a site enabling a search to be performed of the manner detailed below:
User inputs a search term / phrase (string of words but unlikely to be more than 5 or 6)
String is chopped into its constituent words
Entries in a single model with a description (a single field in the model) are output
Having looked at previous questions on this site, I am aware that there are a number of add-ons which are commonly used for search queries, however, are these needed in such a simple situation?
I was thinking that I could use an SQL command with a number of ANDs to perform this task?
Currently the model is stored within sqlite3, but it is probably going to grow to about 100,000 lines (just 10 fields though) in the near future if this is likely to cause problems?
Finally, is there an easy way to pull out the words of a string automatically for any length of string / up to a certain limit that is unlikely to be exceeded?
Thanks in advance for your time and patience
You can easily pull the words from a string with ruby: 'alice bob charlie'.split(/\s+/) will give you an array with the words.
Then, you can string those words together into an SQL query to find the appropriate records. It don't know about the performance of this solution though... You should definitely test it out to see if there are any performance issues.
I have a query which slows down immensely when i add an addition where part
which essentially is just a like lookup on a varchar(500) field
where...
and (xxxxx.yyyy like '% blahblah %')
I've been racking my head but pretty much the query slows down terribly when I add this in.
I'm wondering if anyone has suggestions in terms of changing field type, index setup, or index hints or something that might assist.
any help appreciated.
sql 2000 enterprise.
HERE IS SOME ADDITIONAL INFO:
oops. as some background unfortunately I do need (in the case of the like statement) to have the % at the front.
There is business logic behind that which I can't avoid.
I have since created a full text catalogue on the field which is causing me problems
and converted the search to use the contains syntax.
Unfortunately although this has increased performance on occasion it appears to be slow (slower) for new word searchs.
So if i have apple.. apple appears to be faster the subsequent times but not for new searches of orange (for example).
So i don't think i can go with that (unless you can suggest some tinkering to make that more consistent).
Additional info:
the table contains only around 60k records
the field i'm trying to filter is a varchar(500)
sql 2000 on windows server 2003
The query i'm using is definitely convoluted
Sorry i've had to replace proprietary stuff.. but should give you and indication of the query:
SELECT TOP 99 AAAAAAAA.Item_ID, AAAAAAAA.CatID, AAAAAAAA.PID, AAAAAAAA.Description,
AAAAAAAA.Retail, AAAAAAAA.Pack, AAAAAAAA.CatID, AAAAAAAA.Code, BBBBBBBB.blahblah_PictureFile AS PictureFile,
AAAAAAAA.CL1, AAAAAAAA.CL1, AAAAAAAA.CL2, AAAAAAAA.CL3
FROM CCCCCCC INNER JOIN DDDDDDDD ON CCCCCCC.CID = DDDDDDDD.CID
INNER JOIN AAAAAAAA ON DDDDDDDD.CID = AAAAAAAA.CatID LEFT OUTER JOIN BBBBBBBB
ON AAAAAAAA.PID = BBBBBBBB.Product_ID INNER JOIN EEEEEEE ON AAAAAAAA.BID = EEEEEEE.ID
WHERE
(CCCCCCC.TID = 654321) AND (DDDDDDDD.In_Use = 1) AND (AAAAAAAA.Unused = 0)
AND (DDDDDDDD.Expiry > '10-11-2010 09:23:38') AND
(
(AAAAAAAA.Code = 'red pen') OR
(
(my_search_description LIKE '% red %') AND (my_search_description LIKE '% nose %')
AND (DDDDDDDD.CID IN (63,153,165,305,32,33))
)
)
AND (DDDDDDDD.CID IN (20,32,33,63,64,65,153,165,232,277,294,297,300,304,305,313,348,443,445,446,447,454,472,479,481,486,489,498))
ORDER BY AAAAAAAA.f_search_priority DESC, DDDDDDDD.Priority DESC, AAAAAAAA.Description ASC
You can see throwing in the my_search_description filter also includes a dddd.cid filter (business logic).
This is the part which is slowing things down (from a 1.5-2 second load of my pages down to a 6-8 second load (ow ow ow))
It might be my lack of understanding of how to have the full text search catelogue working.
Am very impressed by the answers so if anyone has any tips I'd be most greatful.
If you haven't already, enable full text indexing.
Unfortunately, using the LIKE clause on a query really does slow things down. Full Text Indexing is really the only way that I know of to speed things up (at the cost of storage space, of course).
Here's a link to an overview of Full-Text Search in SQL Server which will show you how to configure things and change your queries to take advantage of the full-text indexes.
More details would certainly help, but...
Full-text indexing can certainly be useful (depending on the more details about the table and your query). Full Text indexing requires a good bit of extra work both in setup and querying, but it's the only way to try to do the sort of search you seek efficiently.
The problem with LIKE that starts with a Wildcard is that SQL server has to do a complete table scan to find matching records - not only does it have to scan every row, but it has to read the contents of the char-based field you are querying.
With or without a full-text index, one thing can possibly help: Can you narrow the range of rows being searched, so at least SQL doesn't need to scan the whole table, but just some subset of it?
The '% blahblah %' is a problem for improving performance. Putting the wildcard at the beginning tells SQL Server that the string can begin with any legal character, so it must scan the entire index. Your best bet if you must have this filter is to focus on your other filters for improvement.
Using LIKE with a wildcard at the beginning of the search pattern forces the server to scan every row. It's unable to use any indexes. Indexes work from left to right, and since there is no constant on the left, no index is used.
From your WHERE clause, it looks like you're trying to find rows where a specific word exists in an entry. If you're searching for a whole word, then full text indexing may be a solution for you.
Full text indexing creates an index entry for each word that's contained in the specified column. You can then quickly find rows that contain a specific word.
As other posters have correctly pointed out, the use of the wildcard character % within the LIKE expression is resulting in a query plan being produced that uses a SCAN operation. A scan operation touches every row in the table or index, dependant on the type of scan operation being performed.
So the question really then becomes, do you actually need to search for the given text string anywhere within the column in question?
If not, great, problem solved but if it is essential to your business logic then you have two routes of optimization.
Really go to town on increasing the overall selectivity of your query by focusing your optimization efforts on the remaining search arguments.
Implement a Full Text Indexing Solution.
I don't think this is a valid answer, but I'd like to throw it out there for some more experienced posters comments...are these equivlent?
where (xxxxx.yyyy like '% blahblah %')
vs
where patindex(%blahbalh%, xxxx.yyyy) > 0
As far as I know, that's equivlent from a database logic standpoint as it's forcing the same scan. Guess it couldn't hurt to try?
I have a large number of phrases (~ several million), each less than six or seven words and the large majority less than five, and I would like to see if they "phrase match" each other. This is a search engine marketing term - essentially, A phrase matches B if A is contained in B. Right now, they are stored in a db (postgres), and I am performing a join on regexes (see this question). It is running impossibly slowly even after trying all basic optimization tricks (indexing, etc) and trying the suggestions provided.
Is there an easier way to do this? I am not averse to a non-DB solution. Is there any reason to think that regexes are overkill and are taking way longer than a different solution?
An ideal algorithm for doing sub-string matching is AhoCorsick.
Although you will have to read the data out of the database to use it, it is tremendously fast, when compared to more naive methods.
See here for a related question on substring matching:
And here for an AhoCorsick implementation in Java:
It would be great to get a little more context as to why you need to see which phrases are subsets of others: for example, it seems strange that the DB would be built in such a way anyway: you're having to do the work now because the DB is not in an appropriate format, so it makes sense that you should 'fix' the DB or the way in which it is built, instead.
It depends massively on what you are doing with the data and why, but I have found it useful in the past to break things down into single words and pairs of words, then link resources or phrases to those singles/pairs.
For example to implement a search I have done:
Source text: Testing phrases to see
Entries:
testing
testing phrases
phrases
phrases to
to
to see
see
To see if another phrase was similar (granted, not contained within) you would break down the other phrase in the same way and count the number of phrases common between them.
It has the nice side effect of still matching if you were to use (for example) "see phases to testing": because the individual words would match.. but because the order is different the pairs wouldn't, so it's taking phrases (consecutive words) into account at the same time, the number of matches wouldn't be as high, good for use as a 'score' in matching.
As I say that -kind- of thing has worked for me, but it would be great to hear some more background/context, so we can see if we can find a better solution.
When you have the 'cleaned column' from MaasSQL's previous answer, you could, depending on the way "phrase match" works exactly (I don't know), sort this column based on the length of the containing string.
Then make sure you run the comparison query in a converging manner in a procedure instead of a flat query, by stepping through your table (with a cursor) and eliminating candidates for comparison through WHERE statements and through deleting candidates that have already been tested (completely). You may need a temporary table to do this.
What do I mean with 'WHERE' statement previously? Well, if the comparison value is in a column sorted on length, you'll never have to test whether a longer string matches inside a shorter string.
And with deleting candidates: starting with the shortest strings, once you've tested all strings of a certain length, you'll can remove them from the comparison table, as any next test you'll do will never get a match.
Of course, this requires a bit more programming than just one SQL statement. And is dependent on the way "phrase match" works exactly.
DTS or SSIS may be your friend here as well.