suppose we have a file with just one table named TableA and this table has just one column named Text;
let say we populate our TableA with 3,000,000 of strings like these(each line a record):
Many of our patients are incontinent.
Many of our patients are severely disturbed.
Many of our patients need help with dressing.
if I save the file at this level it'll be: ~326 MB
now let say we want to increase the speed of our queries and therefore we set our Text column as the PrimaryKey(or create index on it);
if I save the file at this level it'll be: ~700 MB
our query:
SELECT Text FROM "TableA" where Text like '% home %'
for the table without index: ~5.545s
for the indexed table: ~2.231s
As far as I know when we create index on a column or set a column to be our PrimaryKey then sqlite engine doesn't need to refer to table itself(if no other column was requested in query) and it uses the index for query and hence the speed of query execution increases;
My question is in the scenario above which we have just one column and set that column to be the PrimaryKey too, then why sqlite holds some kind of unnecessary data?(at least it seems unnecessary!)(in this case ~326 MB) why not just keeping the index\PrimaryKey data?
In SQLite, table rows are stored in the order of the internal rowid column.
Therefore, indexes must be stored separately.
In SQLite 3.8.2 or later, you can create a WITHOUT ROWID table which is stored in order of its primary key values.
Related
I have a 3 GB SQLite database. I want to modify column type of one of the table columns.
I know that sqlite does not support altering columns and this can only be done by recreating a table.
That's how I do it:
BEGIN TRANSACTION;
ALTER TABLE tbl RENAME TO tbl_;
CREATE TABLE tbl (a INTEGER, b TEXT, c TEXT);
INSERT INTO tbl SELECT * FROM tbl_;
DROP TABLE tbl_;
COMMIT;
I thought that during this process since I use a transaction then the database size will not increase. But it did. On my disk not enough space to double the database size. Is it normal that the database size increases within the transaction? Is there any other way of modifying column type without increasing database size? This process also takes a lot of time. Unexpectedly, most of the time is taken by DROP TABLE statement, it's even longer than INSERT statement. Why dropping table is longer than copying data from one table to another?
Thanks in advance!
I have a table indexed on a text column, and I want all my queries to return results ordered by name without any performance hit.
Table has around 1 million rows if it matters.
Table -
CREATE TABLE table (Name text)
Index -
CREATE INDEX "NameIndex" ON "Files" (
"Name" COLLATE nocase ASC
);
Query 1 -
select * from table where Name like "%a%"
Query plan, as expected a full scan -
SCAN TABLE table
Time -
Result: 179202 rows returned in 53ms
Query 2, now using order by to read from index -
select * from table where Name like "%a%" order by Name collate nocase
Query plan, scan using index -
SCAN TABLE table USING INDEX NameIndex
Time -
Result: 179202 rows returned in 672ms
Used DB Browser for SQLite to get the information above, with default Pragmas.
I'd assume scanning the index would be as performant as scanning the table, is it not the case or am I doing something wrong?
Another interesting thing I noticed, that may be relevant -
Query 3 -
select * from table where Name like "a%"
Result: 23026 rows returned in 9ms
Query 4 -
select * from table where name like "a%" order by name collate nocase
Result: 23026 rows returned in 101ms
And both has them same query plan -
SEARCH TABLE table USING INDEX NameIndex (Name>? AND Name<?)
Is this expected? I'd assume the performance be the same if the plan was the same.
Thanks!
EDIT - The reason the query is slower was because I used select * and not select name, causing SQLite to go between the table and the index.
The solution was to use clustered index, thanks #Tomalak for helping me find it -
create table mytable (a text, b text, primary key (a,b)) without rowid
The table will be ordered by default using a + b combination, meaning that full scan queries will be much faster (now 90ms).
A LIKE pattern that starts with % can never use an index. It will always result in a full table scan (or index scan, if the query can be covered by the index itself).
It's logical when you think about it. Indexes are not magic. They are sorted lists of values, exactly like a keyword index in a book, and that means they are only only quick for looking up a word if you know how the given word starts. If you're searching for the middle part of a word, you would have to look at every index entry in a book as well.
Conclusion from the ensuing discussion in the comments:
The best course of action to get a table that always sorts by a non-unique column without a performance penalty is to create it without ROWID, and turn it into a clustering index over a the column in question plus a second column that makes the combination unique:
CREATE TABLE MyTable (
Name TEXT COLLATE NOCASE,
Id INTEGER,
Other TEXT,
Stuff INTEGER,
PRIMARY KEY(Name, Id) -- this will sort the whole table by Name
) WITHOUT ROWID;
This will result in a performance penalty for INSERT/UPDATE/DELETE operations, but in exchange sorting will be free since the table is already ordered.
I have two databases with the same structure. The first is the main one, while the second get updated periodically (in reality I have multiple "secondary" databases that I want to merge one by one into the main one).
The structure of the main and the secondary databases is identical.
I want to periodically dump all new values from the secondary database in the main one. However, the second time I do it, I want to exclude rows that were already copied the first time (and so on).
The tables in all these database have:
an ID column set as PRIMARY KEY going from 1 to N for each database (I suspect this was a mistake, but at the moment I can't change this)
a DATE column, representing a posix timestamp (float)
some other columns
My code looks like this:
ATTACH DATABASE secondary.db AS temp_db
DROP TABLE IF EXISTS my_table_temp
CREATE TABLE my_table_temp AS SELECT * FROM my_table
INSERT INTO main.my_table_temp SELECT * FROM temp_db.my_table
DELETE FROM my_table
INSERT INTO main.my_table SELECT DISTINCT * FROM main.my_table_temp ORDER BY date
DROP TABLE my_table_temp
the problem is that - I suspect due to the repeated ID column - the DISTINCT clause returns me:
UNIQUE constraint failed: my_table.id
However I don't care at all of the ID field that could also be dropped or reset.
NOTES:
the secondary databases are constantly updated by a code that - at the moment - I can't change
I initialize the "main" database copy-pasting one of the secondary to avoid regenerating the whole structure from scratch. Maybe there is a better way of doing this
Apologies if this is a naive question, but I'm very new with SQLite.
Thanks
Following the advice from #forpas, I solved this with the following code:
Assuming the columns to be id,date,col1 and col2
ATTACH DATABASE secondary.db AS temp_db
DROP TABLE IF EXISTS my_table_temp
CREATE TABLE my_table_temp AS SELECT date,col1,col2 FROM my_table
INSERT INTO main.my_table_temp SELECT date,col1,col2 FROM temp_db.my_table
DROP TABLE my_table /* I need to recreate my_table as I've removed a column*/
CREATE TABLE main.my_table AS SELECT DISTINCT date,col1,col2 FROM main.my_table_temp ORDER BY date
DROP TABLE my_table_temp
also, I automatized the extraction of the column names doing
SELECT name FROM PRAGMA_TABLE_INFO('my_table');
This is then passed to the python code running the script and the column id is removed from the list. Note that the second (and following) time I run this code, the column id won't be present in my_table to start with. However this approach allows the code to be the same in the two cases: either if the column id is there or not.
This procedure is then iterated over each table name to fully merge the two databases.
My problem is that my querys are too slow.
I have a fairly large sqlite database. The table is:
CREATE TABLE results (
timestamp TEXT,
name TEXT,
result float,
)
(I know that timestamps as TEXT is not optimal, but please ignore that for the purposes of this question. I'll have to fix that when I have the time)
"name" is a category. This calculation holds the results of a calculation that has to be done at each timestamp for all "name"s. So the inserts are done at equal-timestamps, but the querys will be done at equal-names (i.e. I want given a name, get its time series), like:
SELECT timestamp,result WHERE name='some_name';
Now, the way I'm doing things now is to have no indexes, calculate all results, then create an index on name CREATE INDEX index_name ON results (name). The reasoning is that I don't need the index when I'm inserting, but having the index will make querys on the index really fast.
But it's not. The database is fairly large. It has about half a million timestamps, and for each timestamp I have about 1000 names.
I suspect, although I'm not sure, that the reason why it's slow is that every though I've indexed the names, they're still scattered all around the physical disk. Something like:
timestamp1,name1,result
timestamp1,name2,result
timestamp1,name3,result
...
timestamp1,name999,result
timestamp1,name1000,result
timestamp2,name1,result
timestamp2,name2,result
etc...
I'm sure this is slower to query with NAME='some_name' than if the rows were physically ordered as:
timestamp1,name1,result
timestamp2,name1,result
timestamp3,name1,result
...
timestamp499997,name1000,result
timestamp499998,name1000,result
timestamp499999,name1000,result
timestamp500000,namee1000,result
etc...
So, how do I tell SQLite that the order in which I'd like the rows in disk isn't the one they were written in?
UPDATE: I'm further convinced that the slowness in doing a select with such an index comes exclusively from non-contiguous disk access. Doing SELECT * FROM results WHERE name=<something_that_doesnt_exist> immediately returns zero results. This suggests that it's not finding the names that's slow, it's actually reading them from the disk.
Normal sqlite tables have, as a primary key, a 64-bit integer (Known as rowid and a few other aliases). That determines the order that rows are stored in a B*-tree (Which puts all actual data in leaf node pages). You can change this with a WITHOUT ROWID table, but that requires an explicit primary key which is used to place rows in a B-tree. So if every row's (name, timestamp) columns make a unique value, that's a possibility that will leave all rows with the same name on a smaller set of pages instead of scattered all over.
You'd want the composite PK to be in that order if you're searching for a particular name most of the time, so something like:
CREATE TABLE results (
timestamp TEXT
, name TEXT
, result REAL
, PRIMARY KEY (name, timestamp)
) WITHOUT ROWID
(And of course not bothering with a second index on name.) The tradeoff is that inserts are likely to be slower as the chances of needing to split a page in the B-tree go up.
Some pragmas worth looking into to tune things:
cache_size
mmap_size
optimize (After creating your index; also consider building sqlite with SQLITE_ENABLE_STAT4.)
Since you don't have an INTEGER PRIMARY KEY, consider VACUUM after deleting a lot of rows if you ever do that.
So this is essentially a follow-up question on Finding duplicate records.
We perform data imports from text files everyday and we ended up importing 10163 records spread across 182 files twice. On running the query mentioned above to find duplicates, the total count of records we got is 10174, which is 11 records more than what are contained in the files. I assumed about the posibility of 2 records that are exactly the same and are valid ones being accounted for as well in the query. So I thought it would be best to use a timestamp field and simply find all the records that ran today (and hence ended up adding duplicate rows). I used ORA_ROWSCN using the following query:
select count(*) from my_table
where TRUNC(SCN_TO_TIMESTAMP(ORA_ROWSCN)) = '01-MAR-2012'
;
However, the count is still more i.e. 10168. Now, I am pretty sure that the total lines in the file is 10163 by running the following command in the folder that contains all the files. wc -l *.txt.
Is it possible to find out which rows are actually inserted twice?
By default, ORA_ROWSCN is stored at the block level, not at the row level. It is only stored at the row level if the table was originally built with ROWDEPENDENCIES enabled. Assuming that you can fit many rows of your table in a single block and that you're not using the APPEND hint to insert the new data above the existing high water mark of the table, you are likely inserting new data into blocks that already have some existing data in them. By default, that is going to change the ORA_ROWSCN of every row in the block causing your query to count more rows than were actually inserted.
Since ORA_ROWSCN is only guaranteed to be an upper-bound on the last time there was DML on a row, it would be much more common to determine how many rows were inserted today by adding a CREATE_DATE column to the table that defaults to SYSDATE or to rely on SQL%ROWCOUNT after your INSERT ran (assuming, of course, that you are using a single INSERT statement to insert all the rows).
Generally, using the ORA_ROWSCN and the SCN_TO_TIMESTAMP function is going to be a problematic way to identify when a row was inserted even if the table is built with ROWDEPENDENCIES. ORA_ROWSCN returns an Oracle SCN which is a System Change Number. This is a unique identifier for a particular change (i.e. a transaction). As such, there is no direct link between a SCN and a time-- my database might be generating SCN's a million times more quickly than yours and my SCN 1 may be years different from your SCN 1. The Oracle background process SMON maintains a table that maps SCN values to approximate timestamps but it only maintains that data for a limited period of time-- otherwise, your database would end up with a multi-billion row table that was just storing SCN to timestamp mappings. If the row was inserted more than, say, a week ago (and the exact limit depends on the database and database version), SCN_TO_TIMESTAMP won't be able to convert the SCN to a timestamp and will return an error.