I would like to know if there is an efficient way to count the number of rows returned by a batch scanner in Accumulo without having to manually iterate over all rows returned.
What I have at the moment is something like this
Connector connector = // Created a new connector
BatchScanner bsc = connector.createBatchScanner(tableName, Authorizations.EMPTY, numThreads);
/*
... applying filters
*/
Iterator<Map.Entry<Key, Value>> e = bsc.iterator();
long cnt = 0;
while(e.hasNext()) {
cnt++;
}
return cnt;
I am iterating over every row returned by the batch scanner and counting each row that I encounter. What I would like to know is if there is a better way of doing this?
In general (What is the best way to get the count/length/size of an iterator?) you won't be able to do this any faster, as your filter could be anything and thus somewhere you're going to have to do some counting.
There are other ways (Maintain statistics across rows in accumulo) that you can go about keeping track of the counts, but they might introduce new headaches for you.
Related
I'm experiencing a really odd result when I do a count in X++, something I've not experienced before. I am performing what I thought was a really simply count query, but I can't seem to get the result I am after.
WMSOrderTrans orderTrans;
WMSOrderTrans orderTransChk;
;
select count(RecId) from orderTrans group by shipmentid where orderTrans.inventTransRefId == 'XXXXXX';
info(strFmt('Count is %1', orderTrans.RecId));
while select orderTransChk group by shipmentid where orderTransChk.inventTransRefId == 'XXXXXX' {
info(strFmt('Shipment is %1', orderTransChk.shipmentId));
}
The data set that I am selecting all have only 1 shipmentid, so the first select I am expecting a count of 1, instead I get 4 (which is how many lines for that transrefid exist). If I change the count from 'RecId' to 'ShipmentId', then instead of the count, I get actual shipmentId. I simply want it to return the count of the records, which is what I believe I've asked it to do.
I really can't see what I am missing.
In the while select, I get what I expect (the shipmentid), only 1 infolog message for the loop. This tells me that the group by with the where clause is working, but it doesn't explain why the first count select statement isn't behaving as I would expect.
For reference, this is AX2012 R1 system.
For anyone who might be interested in knowing my answer, it's tied up with Jeff's response. At the end of the day, I didn't look at data well enough, and the query returned the correct results. I initially thought there were a number of unique shipments, but I was wrong. My expected result was erroneous. There were 4 lines in the file, but the lines were unique for the item, not the shipment. They were all on the same shipment. So really, my own fault, it goes to show that one really needs to look at the data closely.
Thanks to all that responded, greatly appreciated.
I would try a database sync, then restarting the AOS. I don't see anything obviously wrong, so it points to bouncing everything.
Try getting the select statement via this method (from memory so check syntax) and then review the query against SQL directly. It uses generateOnly.
select generateOnly count(RecId) from orderTrans group by shipmentid where orderTrans.inventTransRefId == 'XXXXXX';
info(orderTrans.getSQLStatement());
If I understand what you try to achieve, you'd like to get something like this SQL query:
select count(distinct shipmentid) from orderTrans
where inventTransRefId = 'XXXXXX'
The 'distinct' keyword is not available in AX select command. The group by clause will allow you to iterate all distinct values but not to use an aggregate on top of it.
You may use a sql connection to push the exact sql command you want.
In AX, aggregate values are stores in the field used: Count(RecId), the count will go in the recid field otherwise the system may need to add new field on the buffer on the fly. I don't think you can aggregate on the group by clause as it's important to have its value.
You can try (I don't have an AX to test it) to use a query:
Query query = new Query();
QueryRun queryRun;
QueryBuildDataSource qbd;
qbd = query.addDataSource(tablenum(OrderTrans));
qbd.addRange(fieldNum(OrderTrans, InventTransId)).value("xxxx");
qbd.addSortField(fieldNum(OrderTrans, ShipmentId));
qbd.SortOrder(SortOrder::GroupBy);
queryRun = new QueryRun(query);
info(strfmt("Total Records in Query %1",SysQuery::countTotal(queryRun)));
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.
I am a newbie using asp.net I have a problem on what I am going to use. The problem is that i should count the number of available rooms in a hotel using SQL I use count but it's not working is there any way to use?
availableRMS.Text = rdr.Item(0)
First first column in the table is at the 0 index, not the 1 index
I know it's not the direct answer to your question, but it'd be much simpler if you just used ExecuteScalar to get your count value, since you only have one row/value being returned:
int count = (int) cmd1.ExecuteScalar();
availableRMS.Text = count;
Since Count will always return a number with your query in SQL Server (zero if no rows), then you don't need all the extra checks required for using the reader.
I have this query:
var newComponents = from ic in importedComponents
where !existingComponents.Contains(ic)
select ic;
importedComponents and existingComponents are of type List<ImportedComponent>, and exist only in memory (are not tied to a data context). In this instance, importedComponents has just over 6,100 items, and existingComponents has 511 items.
This statement is taking too long to complete (I don't know how long, I stop the script after 20 minutes). I've tried the following with no improvement in execution speed:
var existingComponentIDs = from ec in existingComponents
select ec.ID;
var newComponents = from ic in importedComponents
where !existingComponentIDs.Contains(ic.ID)
select ic;
Any help will be much appreciated.
The problem is quadratic complexity of this algorithm. Put the IDs of all existingComponentIDs into a HashSet and use the HashSet.Contains method. It has O(1) lookup cost compared to O(N) for Contains/Any on a list.
The morelinq project contains a method that does all of that in one convenient step: ExceptBy.
You could use Except to get the set difference:
var existingComponentIDs = existingComponents.Select(c => c.ID);
var importedComponentIDs = importedComponents.Select(c => c.ID);
var newComponentIDs = importedComponentIDs.Except(existingComponentIDs);
var newComponents = from ic in importedComponents
join newID in newComponentIDs on ic.ID equals newID
select ic;
foreach (var c in newComponents)
{
// insert into database?
}
Why is LINQ JOIN so much faster than linking with WHERE?
In short: Join method can set up a hash table to use as an index to quicky zip two tables together
Well based on the logic and numbers you provided that means you are basically performing 3117100 comparisons when you run that statement. Obviously that is not entirely accurate because your condition may be satisfied before running through the entire array but you get my point.
With collections this large you are going to want use a collection where you can index your key (in this case your component ID) to help reduce the overhead of the search. The thing to remember is that even though LINQ looks like SQL there are no magic indexes here; it is mainly for convenience. In fact, I have seen articles where a link lookup is actually a slight bit slower than a brute force lookup.
EDIT: If it is possible I would suggest trying a Dictionary or SortedList for your values. I believe either one would have slightly better lookup performance.
I'm using the following code in an ASP.NET page to create a record, then count the records to make sure I haven't exceeded a set limit and rollback the transaction if I have.
using (var session = NhibernateHelper.OpenSession())
using (var transaction = session.BeginTransaction())
{
session.Lock(mall, LockMode.None);
var voucher = new Voucher();
voucher.FirstName = firstName ?? string.Empty;
voucher.LastName = lastName ?? string.Empty;
voucher.Address = address ?? string.Empty;
voucher.Address2 = address2 ?? string.Empty;
voucher.City = city ?? string.Empty;
voucher.State = state ?? string.Empty;
voucher.Zip = zip ?? string.Empty;
voucher.Email = email ?? string.Empty;
voucher.Mall = mall;
session.Save(voucher);
var issued = session.CreateCriteria<Voucher>()
.Add(Restrictions.Eq("Mall", mall))
.SetProjection(Projections.Count("ID"))
.UniqueResult<int>();
if (issued >= mall.TotalVouchers)
{
transaction.Rollback();
throw new VoucherLimitException();
}
transaction.Commit();
return voucher;
}
However, I'm getting a ton of deadlocks. I presume this happens because I'm trying to count the records in a table I just performed an insert on and a lock is still held on the inserted row, causing the deadlock.
Can anyone confirm this?
Can anyone suggest an fix?
I've tried calling SetLockMode(LockMode.None) on the final query, but that results in a NullReferenceException that I cannot figure out.
Edit: If I run the query before I save the object, it works, but then I'm not accomplishing the goal of verifying that my insert didn't somehow go over the limit (in the case of concurrent inserts).
Edit: I found that using IsolationLevel.ReadUncommited in the session.BeginTransaction call solves the problem, but I'm no database expert. Is this the appropriate solution to the problem or should I adjust my logic some how?
That design would be deadlock prone - typically (not always) one connection is unlikely to deadlock itself, but multiple connections that do inserts and aggregates against the same table are very likely to deadlock. That's because while all activity in one transaction looks complete from the point of view of the connection doing the work -- the db won't lock a transaction out of "its own" records -- the aggregate queries from OTHER transactions would attempt to lock the whole table or large portions of it at the same time, and those would deadlock.
Read Uncommitted is not your friend in this case, because it basically says "ignore locks," which at some point will mean violating the rules you've set up around the data. I.E. the count of records in the table will be inaccurate, and you'll act on that inaccurate count. Your count will return 10 or 13 when the real answer is 11.
The best advice I have is to rearrange your insert logic such that you capture the idea of the count, without literally counting the rows. You could go a couple of directions. One idea I have is this: literally number the inserted vouchers with a sequence and enforce a limit on the sequence itself.
Make a sequence table with columns (I am guessing) MallID, nextVoucher, maxVouchers
Seed that table with the mallids, 1, and whatever the limit is for each mall
Change the insert logic to this pseudo code:
Begin Transaction
Sanity check the nextVoucher for Mall in the sequence table; if too many exist abort
If less than MaxVouchers for Mall then {
check, fetch, lock and increment nextVoucher
if increment was successful then use the value of nextVoucher to perform your insert.
Include it in the target table.
}
Error? Rollback
No Error? Commit
A sequence table like this hurts concurrency some, but I think not as much as counting the rows in the table constantly. Be sure to perf test.
Also, the [check, fetch, lock and increment] is important - you have to exclusively lock the row in the sequence table to prevent some other connection from using the same value in the split second before you increment it. I know the SQL syntax for this, but I'm afraid I am no nHibernate expert.
For read uncommitted data errors, check this out: http://sqlblog.com/blogs/merrill_aldrich/archive/2009/07/29/transaction-isolation-dirty-reads-deadlocks-demo.aspx (disclaimer: Merrill Aldrich is me :-)
2 questions :
How frequently are vouchers deleted
Any objections (beyond purity) to a
db level trigger ?