I output the query plan on SQLite, and it shows
0|0|0|SCAN TABLE t (~500000 rows)
I wonder what is the meaning of the number (500000)? I guess it is the table length, but I executed the query on a small table which does not have so many rows.
Is there any official document about the meaning of the number? thanks.
As the official documentation says, this is the number of rows that the database estimates will be returned.
If there is an index on a seached column, and if you have run ANALYZE, then SQLite can make an estimate based on the actual data. Otherwise, it assumes that tables contain one million rows, and that a search like column > x filters out half the rows.
Related
Problem
Can't create a table with an index column that references multiple rows in a table. Picture example below of what I'm trying to create.
Overview
Imagine an (SQLite) table will hold stock dividend payments. The index column is set to the ticker symbols. However, each ticker symbol refers to multiple records, which are organized by a time stamp. The documentation on SQLite and about 15 other tutorials all seem to focus on indexing where there is always a 1:1 relationship between an index and a record. I would like to create an index with a 1:many relationship.
The lookup would find the appropriate stock by symbol, and then (probably) a secondary index on the dates in the first column. But I cannot find any examples where others have tried to set up this structure. Makes me think maybe I don't have the right approach, or this is just a special case.
I don't think your problem is actually a problem. Putting an index on a column doesn't mean it has to contain unique values. It's perfectly reasonable for values in an indexed column to repeat. Of course there are diminishing returns. E.g. If you have a million rows and only five different values in a column, an index on that column isn't really going to do much for you.
A good rule of thumb is to start with an index on the column(s) you're using in your where clause. Then run the queries and see if you're getting satisfactory performance.
I have to prepare a table where I will keep weekly results for some aggregated data. Table will have 30 fields (10 CHARACTERs, 20 DECIMALs), I think I will have 250k rows weekly.
In my head I can see two scenarios:
Set table and relying on teradata in preventing duplicate rows - it should skip duplicate entries while inserting new data
Multi set table with UPI - it will give an error upon inserting duplicate row.
INSERT statement is going to be executed through VBA on excel, where handling possible teradata errors is not a problem.
Which scenario will be faster to run in a year time where there will be circa 14 millions rows
Is there any other way to have it done?
Regards
On a high level, since you would be having a comparatively high data count on your table, it is advisable not to use SET tables, rather go with the multiset table.
For more info you can refer to this link
http://www.dwhpro.com/teradata-multiset-tables/
Why do you care about Duplicate Rows? When you store weekly aggregates there should be no duplicates at all. And Duplicate Rows are not the same as duplicate Primary Key values.
Simply choose a PI which fits best your join/access pattern (maybe partition by date). To avoid any potential duplicates you might simply use MERGE instead of INSERT.
I'm attaching a database (B) to another database (A) and trying to populate an empty table in A by doing something like:
INSERT INTO table SELECT * FROM B.table
SQLite's documentation mentions this, but it doesn't mention any limit on the number of rows returned by the SELECT statement (or processable by an INSERT statement in this particular scenario).
Is there any limit on this number of rows, or can I assume that all rows returned by the SELECT query will indeed be inserted?
(please note that I'm not looking for alternative ways of copying the data, I really just want to know whether or not I may bump into any unexpected limits here)
There is no limit, excluding the general limits for SQLite, that can be seen in this page: https://www.sqlite.org/limits.html , for instance:
The theoretical maximum number of rows in a table is 2^64 (18446744073709551616 or about 1.8e+19). This limit is unreachable since the maximum database size of 140 terabytes will be reached first. A 140 terabytes database can hold no more than approximately 1e+13 rows, and then only if there are no indices and if each row contains very little data.
And since you are getting rows from a SQLite table, there is no practical limit.
How can I get a random record from a table in sqlite for current day. This is for something like "Word of the day". So, I get a random record from db for today, a different random record tomorrow.
I've seen ORDER BY RAND(20120714) LIMIT 1 which works in MySQL, but I'd like to know if its possible to do this in SQLite.
Thanks in advance.
SQLite does not allow to seed its random number generator.
You have to compute the random number in your own code.
This is easy only if the records have consecutive numbers, i.e., autoincrementing IDs; you should change your database.
When performing a SQLite query does the size of the returned data set affect how long the query takes? Lets assume for this question that I don't actually access any of the data in the result, I just want to know if the query itself takes longer. Lets also assume that I am simply selecting all rows and have no WHERE or ORDER BY clauses.
For example if I have two tables A and B. Let says table A has a million rows and table B has 10 rows and that both tables have the same number and types of columns. Will selecting all rows in table A take longer than selecting all rows in table B?
This is a follow up to my question How does a cursor refer to deleted rows?. I am guessing that if a during the query SQLite makes a copy of the data then queries that return large data sets may take longer, unless there is an optimization that only copies the query result data if there is a change to the data in the db while the query is still alive?
Depending on some details, yes, a query may take different amounts of time.
Example: I have a table with some 20k entries. I do a GLOB search that must try every line, with a LIMIT. If the LIMIT is met, the query can stop early. If not, it must go through the entire table (or JOIN). So searches with too many results return quicker than searches with only a few results.
If the query must run through the same amount of data, I don't expect there is a significant difference between a smaller and larger amount of selected rows. There will probably be IO cost, of course.