Is there any way to delete key-value pair where the key start with sub-string1 and ends with sub-string2 in BerkeleyDB without iterating through all the keys in the DB?
For ex:
$sub1 = "B015";
$sub2 = "5646";
I want to delete
$key = "B015HGUJJ75646"
Note: It is guaranteed that there will be only one key for the combination of $sub1 and $sub2.
This can be done by taking an iterator of the DB and checking every key for the condition, but that will be very in-efficient for large DBs. Is there any way to do it without iterating through the complete DB?
If you're using a RECNO database, you're probably out of luck. But, if you can use a BTREE, you have a couple of options.
First, and probably easiest is to iterate over only the portion of the database that makes sense. Assuming you're using the default key comparison function, you can use DB_SET_RANGE to position the starting cursor (iterator) at the start of your partial key string. In your example, this might be "B0150000000000". You then scan forwards with DB_NEXT, looking at each key in turn. When either you find the key you're looking for, or if the key you find doesn't start with "B015", you're done.
Another technique that could be applicable to your situation is to redefine the key comparison function. If, as you state, there is only one combination of $sub1 and $sub2, then perhaps you only need to compare those sections of the keys to guarantee uniqueness? Here's an example of a full string comparison (I'm assuming you're using perl, just from the syntax you supplied above) from https://www2.informatik.hu-berlin.de/Themen/manuals/perl/DB_File.html :
sub Compare
{
my ($key1, $key2) = #_ ;
"\L$key1" cmp "\L$key2" ;
}
$DB_BTREE->{compare} = 'Compare' ;
So, if you can rig things such that you're only comparing the starting and ending four characters, you should be able to drop the database iterator directly onto the key you're interested in.
Related
I've been reading a DynamoDB docs and was unable to understand if it does make sense to query on Global Secondary Index with a usage of 'contains' operator.
My problem is as follows: my dynamoDB document has a list of embedded objects, every object has a 'code' field which is unique:
{
"entities":[
{"code":"entity1Code", "name":"entity1Name"},
{"code":"entity2Code", "name":"entity2Name"}
]
}
I want to be able to get all documents that contain entities with entity.code = X.
For this purpose I'm considering adding a Global Secondary Index that would contain all entity.codes that are present in current db document separated by a comma. So the example above would look like:
{
"entities":[
{"code":"entity1Code", "name":"entity1Name"},
{"code":"entity2Code", "name":"entity2Name"}
],
"entitiesGlobalSecondaryIndex":"entityCode1,entityCode2"
}
And then I would like to apply filter expression on entitiesGlobalSecondaryIndex something like: entitiesGlobalSecondaryIndex contains entityCode1.
Would this be efficient or using global secondary index does not make sense in this way and DynamoDB will simply check the condition against every document which is similar so scan?
Any help is very appreciated,
Thanks
The contains operator of a query cannot be run on a partition Key. In order for a query to use any sort of operators (contains, begins with, > < ect...) you must have a range attributes- aka your Sort Key.
You can very well set up a GSI with some value as your PK and this code as your SK. However, GSIs are replication of the table - there is a slight potential for the data ina GSI to lag behind that of the master copy. If the query you're doing against this GSI isn't very often, then you're probably safe from that.
However. If you are trying to do this to the entire table at once then it's no better than a scan.
If what you need is a specific Code to return all its documents at once, then you could do a GSI with that as the PK. If you add a date field as the SK of this GSI it would even be time sorted. If you query against that code in that index, you'll get every single one of them.
Since you may have multiple codes, if they aren't too many per document, you maybe could use a Sparse Index - if you have an entity with code "AAAA" then you also have an attribute named AAAA (or AAAAflag or something.) It is always null/does not exist Unless the entities contains that code. If you do a GSI on this AAAflag attribute, it will only contain documents that contain that entity code, and ignore all where this attribute does not exist on a given document. This may work for you if you can also provide a good PK on this to keep the numbers well partitioned and if you don't have too many codes.
Filter expressions by the way are different than all of the above. Filter expressions are run on tbe data that would be returned, after it is already read out of the table. This is useful I'd you have a multi access pattern setup, but don't want a particular call to get all the documents associated with a particular PK - in the interests of keeping the data your code is working with concise. The query with a filter expression still retrieves everything from that query, but only presents what makes it past the filter.
If are only querying against a particular PK at any given time and you want to know if it contains any entities of x, then a Filter expressions would work perfectly. Of course, this is only per PK and not for your entire table.
If all you need is numbers, then you could do a count attribute on the document, or a meta document on that partition that contains these values and could be queried directly.
Lastly, and I have no idea if this would work or not, if your entities attribute is a map type you might very well be able to filter against entities code - and maybe even with entities.code.contains(value) if it was an SK - but I do not know if this is possible or not
I have created a table with sqlite for my corona/lua app. It's a hashtable with ~=700 000 values.The table has two columns, which are the hashcode (a string), and the value (another string). During the program I need to get data several times by providing the hashcode.
I'm using something like this code to get the data:
for p in db:nrows([[SELECT * FROM test WHERE id=']].."hashcode"..[[';]]) do
print(p)
-- p = returned value --
end
This statement is though taking insanely too much time to perform
thanks,
Edit:
Success!
the mistake was with the primare key thing.I set the hashcode as the primary key like below and the retrieve time whent to normal:
CREATE TABLE IF NOT EXISTS test (id STRING PRIMARY KEY , array);
I also prepared the statements in advance as you said:
stmt = db:prepare("SELECT * FROM test WHERE id = ?;")
[...]
stmt:bind(1,s)
for p in stmt:nrows() do
The only problem was that the db file size,that was around 18 MB, went to 29,5 MB
You should create the table with id as a unique primary key; this will automatically make an index.
create table if not exists test
(
id text primary key,
val text
);
You should not construct statements using string concatenation; this is a security issue so avoid getting in this habit. Also, you should prepare statements in advance, at program initialization, and run the prepared statements.
Something like this... initially:
hashcode_query_stmt = db:prepare("SELECT * FROM test WHERE id = ?;")
then for each use:
hashcode_query_stmt:bind_values(hashcode)
for p in hashcode_query_stmt:urows() do ... end
Ensure that there is an index on the id/hashcode column? Without one such queries will be slow, slow, slow. This index should probably be unique.
If only selecting the value/hashcode (SELECT value FROM ..), it may be beneficial to have a covering index over (id, value) as that can avoid additional seeking to the row data (see SQLite Query Planning). Try it with and without such a covering index.
Also, it may be worthwhile to employ caching if the same hashcodes are queried multiple times.
As already stated, get sure you have an index on ID.
If you can't change table schema now, you can add a index ad hoc:
CREATE INDEX test_id ON test (id);
About hashes: if you are computing hashes in your software to speed up searches, don't!
SQLite will use your supplied hashes as any regular string/blob. Also, RDBMS are optimized for efficient searching, which may be greatly improved with indexes.
Unless your hashing to save space, you are wasting processor time computing hashes in your application.
I have following declaration for collection
TYPE T_TABLE1 IS TABLE OF TABLE_1%ROWTYPE INDEX BY BINARY_INTEGER;
tbl1_u T_TABLE1;
tbl1_i T_TABLE1;
This table will keep growing and at the end, will be used in FORALL loop to do insert or update on TABLE_1.
Now there might be cases, where I want to delete a certain element. So i am planning to create a procedure, which will take the KEY (unique) and matched the element if that key is found
PSEDUO CODE
FOR i in tbl1_u.FIST..tbl1_u.LAST
LOOP
if tbl1_u(i).key = key then
tbl1.delete(i);
end if;
END LOOP;
My question is,
Once i delete the particular element, would be collection adjust automatically i.e., the index i would be replaced by next element or would that particular index will remain null/invalid and could possibly give me exception if i use it in FORALL INSERT/UPDATE?
I don't think that i can pass TABLE_1%ROWTYPE object to a procedure, do i have to create a record type ?
Any other tip regarding managing collection for bull delete/update/insert would be appreciate. Remeber, I would be dealing with 2 tables, if i am inserting/updating in table_1 then it means i am deleting it from table_2 and vice-versa.
Given that TABLE_1.KEY is unique you might consider using that as the index to your associative arrays. That way you can delete from the collections using the KEY value, which according to the pseudocode is available when doing the deletions. This would also save you having to iterate through the table to find the KEY you want, as the KEY would be the index - so your "deletion" pseudo-code would become:
tbl1_u.delete(key);
To answer your questions:
Since you're using associative arrays, when an element is deleted there is no "empty" space in the collection. The indexes for the elements, however, don't actually change. Therefore you need to use the collection.PRIOR and collection.NEXT methods to loop through the collection. But again, if you use the KEY value as the index you may not need to loop through the collections at all.
You can pass a TABLE_1%ROWTYPE as a parameter to a PL/SQL procedure or function.
You might want to consider using a MERGE statement which could handle doing the inserts and updates in one step. This might allow you to maintain only a single collection. Might be worth looking in to.
Share and enjoy.
I'm creating a caching system to take data from an SQLite database table using a sorted/filtered query and display it. The tables I'm pulling from can be potentially very large and, of course, I need to minimize impact on memory by only retaining a maximum number of rows in memory at any given time. This is easily done by using LIMIT and OFFSET to load only the records I need and update the cache as needed. Implementing this is trivial. The problem I'm having is determining where the insertion index is for a new record inserted into a particular query so I can update my UI appropriately. Is there an easy way to do this? So far the ideas I've had are:
Dump the entire cache, re-count the Query results (there's no guarantee the new row will be included), refresh the cache and refresh the entire UI. I hope it's obvious why that's not really desirable.
Use my own algorithm to determine whether the new row is included in the current query, if it is included in the current cached results and at what index it should be inserted into if it's within the current cached scope. The biggest downfall of this approach is it's complexity and the risk that my own sorting/filtering algorithm won't match SQLite's.
Of course, what I want is to be able to ask SQLite: Given 'Query A' what is the index of 'Row B', without loading the entire query results. However, so far I haven't been able to find a way to do this.
I don't think it matters but this is all occurring on an iOS device, using the objective-c programming language.
More Info
The Query and subsequent cache is based off of user input. Essentially the user can re-sort and filter (or search) to alter the results they're seeing. My reticence in simply recreating the cache on insertions (and edits, actually) is to provide a 'smoother' UI experience.
I should point out that I'm leaning toward option "2" at the moment. I played around with creating my own caching/indexing system by loading all the records in a table and performing the sort/filter in memory using my own algorithms. So much of the code needed to determine whether and/or where a particular record is in the cache is already there, so I'm slightly predisposed to use it. The danger lies in having a cache that doesn't match the underlying query. If I include a record in the cache that the query wouldn't return, I'll be in trouble and probably crash.
You don't need record numbers.
Save the values of the ordered field in the first and last records of the LIMITed query result.
Then you can use these to check whether the new record falls into this range.
In other words, assuming that you order by the Name field, and that the original query was this:
SELECT Name, ...
FROM mytab
WHERE some_conditions
ORDER BY Name
LIMIT x OFFSET y
then try to get at the new record with a similar query:
SELECT 1
FROM mytab
WHERE some_conditions
AND PrimaryKey = LastInsertedValue
AND Name BETWEEN CachedMin AND CachedMax
Similarly, to find out before (or after) which record the new record was inserted, start directly after the inserted record and use a limit of one, like this:
SELECT Name
FROM mytab
WHERE some_conditions
AND Name > MyInsertedName
AND Name BETWEEN CachedMin AND CachedMax
ORDER BY Name
LIMIT 1
This doesn't give you a number; you still have to check where the returned Name is in your cache.
Typically you'd expect a cache to be invalidated if there were underlying data changes. I think dropping it and starting over will be your simplest, maintainable solution. I would recommend it unless you have a very good reason.
You could write another query that just returned the row count (example below) to see if your cache should be invalidated. That would save recreating the cache when it did not change.
SELECT name,address FROM people WHERE area_code=970;
SELECT COUNT(rowid) FROM people WHERE area_code=970;
The information you'd need from sqlite to know when your cache was invalidated would require some rather intimate knowledge of how the query and/or index was working. I would say that is fairly high coupling.
Otherwise, you'd want to know where it was inserted with regards to the sorting. You would probably key each page on the sorted field. Delete anything greater than the insert/delete field. Any time you change the sorting you'd drop everything.
Something like the below would be a start if you were using C++. I realize you aren't doing C++, but hopefully it is evident as to what I'm trying to do.
struct Person {
std::string name;
std::string addr;
};
struct Page {
std::string key;
std::vector<Person> persons;
struct Less {
bool operator()(const Page &lhs, const Page &rhs) const {
return lhs.key.compare(rhs.key) < 0;
}
};
};
typedef std::set<Page, Page::Less> pages_t;
pages_t pages;
void insert(const Person &person) {
if (sql_insert(person)) {
pages_t::iterator drop_cache_start = pages.lower_bound(person);
//... drop this page and everything after it
}
}
You'd have to do some wrangling to get different datatypes of key to work nicely, but its possible.
Theoretically you could just leave the pages out of it and only use the objects themselves. The database would no longer "own" the data though. If you only fill pages from the database, then you'll have less data consistency worries.
This may be a bit off topic, you aren't re-implementing views are you? It doesn't cache per se, but it isn't clear if that is a requirement of your project.
The solution I came up with is not exactly simple, but it's currently working well. I realized that the index of a record in a Query Statement is also the Count of all it's previous records. What I needed to do was 'convert' all the ORDER statements in the query to a series of WHERE statements that would return only the preceding records and take a count of those records. It's trickier than it sounds (or maybe not...it sounds tricky). The biggest issue I had was making sure the query was, in fact, sorted in a way I could predict. This meant I needed to have an order column in the Order Parameters that was based off of a column with unique values. So, whenever a user sorts on a column, I append to the statement another order parameter on a unique column (I used a "Modified Date Stamp") to break ties.
Creating the WHERE portion of the statement requires more than just tacking on a bunch of ANDs. It's easier to demonstrate. Say you have 3 Order columns: "LastName" ASC, "FirstName" DESC, and "Modified Stamp" ASC (the tie breaker). The WHERE statement would have to look something like this ('?' = record value):
WHERE
"LastName" < ? OR
("LastName" = ? AND "FirstName" > ?) OR
("LastName" = ? AND "FirstName" = ? AND "Modified Stamp" < ?)
Each set of WHERE parameters grouped together by parenthesis are tie breakers. If, in fact, the record values of "LastName" are equal, we must then look at "FirstName", and finally "Modified Stamp". Obviously, this statement can get really long if you're sorting by a bunch of order parameters.
There's still one problem with the above solution. Mathematical operations on NULL values always return false, and yet when you sort SQLite sorts NULL values first. Therefore, in order to deal with NULL values appropriately you've gotta add another layer of complication. First, all mathematical equality operations, =, must be replace by IS. Second, all < operations must be nested with an OR IS NULL to include NULL values appropriately on the < operator. This turns the above operation into:
WHERE
("LastName" < ? OR "LastName" IS NULL) OR
("LastName" IS ? AND "FirstName" > ?) OR
("LastName" IS ? AND "FirstName" IS ? AND ("Modified Stamp" < ? OR "Modified Stamp" IS NULL))
I then take a count of the RowID using the above WHERE parameter.
It turned out easy enough for me to do mostly because I had already constructed a set of objects to represent various aspects of my SQL Statement which could be assembled to generate the statement. I can't even imagine trying to manipulate a SQL statement like this any other way.
So far, I've tested using this on several iOS devices with up to 10,000 records in a table and I've had no noticeable performance issues. Of course, it's designed for single record edits/insertions so I don't really need it to be super fast/efficient.
What are they and how do they work?
Where are they used?
When should I (not) use them?
I've heard the word over and over again, yet I don't know its exact meaning.
What I heard is that they allow associative arrays by sending the array key through a hash function that converts it into an int and then uses a regular array. Am I right with that?
(Notice: This is not my homework; I go too school but they teach us only the BASICs in informatics)
Wikipedia seems to have a pretty nice answer to what they are.
You should use them when you want to look up values by some index.
As for when you shouldn't use them... when you don't want to look up values by some index (for example, if all you want to ever do is iterate over them.)
You've about got it. They're a very good way of mapping from arbitrary things (keys) to arbitrary things (values). The idea is that you apply a function (a hash function) that translates the key to an index into the array where you store the values; the hash function's speed is typically linear in the size of the key, which is great when key sizes are much smaller than the number of entries (i.e., the typical case).
The tricky bit is that hash functions are usually imperfect. (Perfect hash functions exist, but tend to be very specific to particular applications and particular datasets; they're hardly ever worthwhile.) There are two approaches to dealing with this, and each requires storing the key with the value: one (open addressing) is to use a pre-determined pattern to look onward from the location in the array with the hash for somewhere that is free, the other (chaining) is to store a linked list hanging off each entry in the array (so you do a linear lookup over what is hopefully a short list). The cases of production code where I've read the source code have all used chaining with dynamic rebuilding of the hash table when the load factor is excessive.
Good hash functions are one way functions that allow you to create a distributed value from any given input. Therefore, you will get somewhat unique values for each input value. They are also repeatable, such that any input will always generate the same output.
An example of a good hash function is SHA1 or SHA256.
Let's say that you have a database table of users. The columns are id, last_name, first_name, telephone_number, and address.
While any of these columns could have duplicates, let's assume that no rows are exactly the same.
In this case, id is simply a unique primary key of our making (a surrogate key). The id field doesn't actually contain any user data because we couldn't find a natural key that was unique for users, but we use the id field for building foreign key relationships with other tables.
We could look up the user record like this from our database:
SELECT * FROM users
WHERE last_name = 'Adams'
AND first_name = 'Marcus'
AND address = '1234 Main St'
AND telephone_number = '555-1212';
We have to search through 4 different columns, using 4 different indexes, to find my record.
However, you could create a new "hash" column, and store the hash value of all four columns combined.
String myHash = myHashFunction("Marcus" + "Adams" + "1234 Main St" + "555-1212");
You might get a hash value like AE32ABC31234CAD984EA8.
You store this hash value as a column in the database and index on that. You now only have to search one index.
SELECT * FROM users
WHERE hash_value = 'AE32ABC31234CAD984EA8';
Once we have the id for the requested user, we can use that value to look up related data in other tables.
The idea is that the hash function offloads work from the database server.
Collisions are not likely. If two users have the same hash, it's most likely that they have duplicate data.