Prevent two threads from selecting same row ibm db2 - db2

I have a situation where I have multiple (potentially hundreds) threads repeating the same task (using a java scheduled executor, if you are curious). This task entails selecting rows of changes (from a table called change) that have not yet been processed (processed changes are kept track in a m:n join table called process_change_rel that keeps track of the process id, record id and status) processing them, then updating back the status.
My question is, how is the best way to prevent two threads from the same process from selecting the same row? Will the below solution (using for update to lock rows ) work? If not, please suggest a working solution
Create table change(
—id , autogenerated pk
—other fields
)
Create table change_process_rel(
—change id (pk of change table)
—process id (pk of process table)
—status)
Query I would use is listed below
Select * from
change c
where c.id not in(select changeid from change_process_rel with cs) for update
Please let me know if this would work

You have to "lock" a row which you are going to process somehow. Such a "locking" should be concurrent of course with minimum conflicts / errors.
One way is as follows:
Create table change
(
id int not null generated always as identity
, v varchar(10)
) in userspace1;
insert into change (v) values '1', '2', '3';
Create table change_process_rel
(
id int not null
, pid int not null
, status int not null
) in userspace1;
create unique index change_process_rel1 on change_process_rel(id);
Now you should be able to run the same statement from multiple concurrent sessions:
SELECT ID
FROM NEW TABLE
(
insert into change_process_rel (id, pid, status)
select c.id, mon_get_application_handle(), 1
from change c
where not exists (select 1 from change_process_rel r where r.id = c.id)
fetch first 1 row only
with ur
);
Every such a statement inserts 1 or 0 rows into the change_process_rel table, which is used here as a "lock" table. The corresponding ID from change is returned, and you may proceed with processing of the corresponding event in the same transaction.
If the transaction completes successfully, then the row inserted into the change_process_rel table is saved, so, the corresponding id from change may be considered as processed. If the transaction fails, the corresponding "lock" row from change_process_rel disappears, and this row may be processed later by this or another application.
The problem of this method is, that when both tables become large enough, such a sub-select may not work as quick as previously.
Another method is to use Evaluate uncommitted data through lock deferral.
It requires to place the status column into the change table.
Unfortunately, Db2 for LUW doesn't have SKIP LOCKED functionality, which might help with such a sort of algorithms.
If, let's say, status=0 is "not processed", and status<>0 is some processing / processed status, then after setting these DB2_EVALUNCOMMITTED and DB2_SKIP* registry variables and restart the instance, you may "catch" the next ID for processing with the following statement.
SELECT ID
FROM NEW TABLE
(
update
(
select id, status
from change
where status=0
fetch first 1 row only
)
set status=1
);
Once you get it, you may do further processing of this ID in the same transaction as previously.
It's good to create an index for performance:
create index change1 on change(status);
and may be set this table as volatile or collect distribution statistics on this column in addition to regular statistics on table and its indexes periodically.
Note that such a registry variables setting has global effect, and you should keep it in mind...

Related

Best way to model state changes for point in time queries

I'm working on a system that needs to be able to find the "state" of an item at a particular time in history. The state is binary (either on or off). In this case it's to determine where to direct (to a particular "keyspace") a piece of timestamped data as determined by the timestamp of the data. I'm having a hard time deciding what the best way to model the data is.
Method 1 is to use the tstzrange with state being implied by the bounds of the range:
create extension btree_gist;
create table core.range_director (
range tstzrange,
directee_id text,
keyspace text,
-- allow a directee to be directed to multiple keyspaces at once
exclude using gist (directee_id with =, keyspace with =, range with &&)
);
insert into core.range_director values
('[2021-01-15 00:00:00 -0:00,2021-01-20 00:00:00 -0:00)', 'THING_ID', 'KEYSPACE_1'),
('[2021-01-15 00:00:00 -0:00,)', 'THING_ID', 'KEYSPACE_2');
select keyspace from core.range_director
where directee_id = 'THING_ID' and range_director.range #> '2021-01-15'::timestamptz;
-- returns KEYSPACE_1 and KEYSPACE_2
select keyspace from core.range_director
where directee_id = 'THING_ID' and range_director.range #> '2021-01-21'::timestamptz;
-- returns KEYSPACE_2
Method 2 is to have explicit state changes:
create table core.status_director (
status_time timestamptz,
status text,
directee_id text,
keyspace text
); -- not sure what pk to use for this method
insert into core.status_director values
('2021-01-15 00:00:00 -0:00','Open','THING_ID','KEYSPACE_1'),
('2021-01-20 00:00:00 -0:00','Closed','THING_ID','KEYSPACE_1'),
('2021-01-15 00:00:00 -0:00','Open','THING_ID','KEYSPACE_2');
select distinct on(keyspace) keyspace, status from core.status_director
where directee_id = 'THING_ID'
and status_time < '2021-01-16'
order by keyspace, status_time desc;
-- returns KEYSPACE_1:Open KEYSPACE_2:Open
select distinct on(keyspace) keyspace, status from core.status_director
where directee_id = 'THING_ID'
and status_time < '2021-01-21'
order by keyspace, status_time desc;
-- returns KEYSPACE_1:Closed, KEYSPACE_2:Open
-- so, client code has to ensure that it only directs to status=Open keyspaces
Maybe there are other methods that would work as well, but these two seem to make the most sense to me. The benefit of the first method is the really easy query, but the down side is that you now have to update rows to close the state whereas in the second method you can just post new states which seems easier.
The table could conceivable grow into thousands or tens of thousands of rows, but will probably not grow into millions (but does the best method change depending on the expected row count?). I have a couple of similar tables with the same point-in-time "state" queries so it's really important that I get the model for them right.
My instinct is to go with Method 1, but are there any footguns or performance considerations that I'm not thinking of that would urge the use case towards Method 2 (or another method I haven't considered?)
No footguns with Method 1, just great big huge cannons. With that method how do you determine the current status. You need to scan each status change and for each one toggle the status, or perhaps use something like "count(*)%2" odd gives one state even another. What happens if any row gets deleted, or data purged and you do not know how many state transactions there were. With the Method 2 you retrieve the greatest date and directly obtain the status.
For myself I would do Method 3. That being Method1 + Method 2. Yes I would have a date range of the status and the status value itself. That gives me complex historical analysis as I have the complete history as well as direct access to current status at any time.
So after doing a bunch of research on the topic I found that my case is a variation of a "Valid-Time State Table". See ch. 2 and ch. 5 of Developing Time-Oriented Database Applications in SQL by Richard Snodgrass.
The support for these tables isn't great but it's not terrible either (at least PostgreSQL has tstzranges to work with). Method 1 of my post is largely sufficient - the main wrinkle is between the state table and other tables.
Since PostgreSQL doesn't have native support for these kinds of temporal tables, you have to build referential integrity yourself. There's a bunch of ways to do this, but for anyone in the future looking for some direction, here is an example of what that might look like for a referential query on two bitemporal tables:
create table a (
row_id bigserial, -- to track individual rows
id int,
pov tstzrange, -- period of validity
pop tstzrange -- period of presence
);
create table b (
row_id bigserial,
id int,
pov tstzrange,
pop tstzrange,
a_id int
);
-- are we good?
with each_pov as (
select bool_or(a.pov #> b.pov) as ok
from a
join b on a.id = b.a_id
and upper(a.pop) is null
and upper(b.pop) is null
group by b.pov
) select coalesce(
bool_and(each_pov.ok),
(select count(*) = 0 from b where upper(pop) is null)
) from each_pov;
You can put the query into a constraint trigger on both the main table and the referenced table to get something approaching sequenced referential integrity for the current period of presence.

Concurrent queries give out unexpected data

I execute several processes to continuously (update + select) data from postgresql (with autocommit option enabled), and get data which should already be filtered out by executing previous update done by other processes.
This is essentially a queue, with all rows initially having status=0, and selected row-by-row in some complicated (not shown) order. Each pending row is set status=1, pid=(process id) and uniqueid=(some iterating id), but different processes for some reason share same rows.
Oversimplified (but still incorrectly working) example is below:
Table definition:
create table Todq (
id bigserial primary key,
url varchar(1024),
status integer not null,
pid integer,uniqueid bigint,
priority integer
);
create index Iodq1 on Todq (status,priority,id);
create index Iodq2 on Todq (pid,uniqueid);
Update (gets next element in queue, sets process pid and iterating uniqueid):
update Todq odq2
set status=1,pid=?,uniqueid=?
from (
select odq.id
from Todq odq
where odq.status=0
order by odq.priority desc,odq.id
limit 1
) odq1
where odq2.id=odq1.id
Select (selects by process id and incrementable uniqueid):
select odq.id,odq.url,odq.pid,odq.uniqueid
from Todq odq
where odq.status=1 and pid=? and uniqueid=?
I made a test bench in perl, which writes values selected to logs/$$.log and as a result different logs share same entries (though with different pid and uniqueid).
The answer is to use (select .. for update) like:
update Todq odq2
set status=1,pid=?,uniqueid=?
from (
select odq.id
from Todq odq
where odq.status=0
order by odq.priority desc,odq.id
limit 1
for update
) odq1
where odq2.id=odq1.id

PostgreSql 9.3 -> several consumers + locking

There are 2 tables:
CREATE TABLE "job"
(
"id" SERIAL,
"processed" BOOLEAN NOT NULL,
PRIMARY KEY("id")
);
CREATE TABLE "job_result"
(
"id" SERIAL,
"job_id" INT NOT NULL,
PRIMARY KEY("id")
);
There are several consumers, that do the following (sequentially):
1) start transaction
2) search for job not processed yet
3) process it
4) save result ( set processed field to true and insert into job_result )
5) commit
Questions:
1) Is the following sql code correct, so no job could be processed more than one time?
2) If it is correct, can it be rewritten in more clean way ? ( I am confused about "UPDATE job SET id = id" )
UPDATE job
SET id = id
WHERE id =
(
SELECT MIN(id)
FROM job
WHERE processed = false AND pg_try_advisory_lock(id) = true
)
AND processed = false
RETURNING *
Thanks.
with job_update as (
update job
set processed = true
where id = (
select id
from (
select min(id)
from job
where processed = false
) s
for update
)
returning id
)
insert into job_result (job_id)
select id
from job_update
Question 1
To answer your first question, the processing can be done twice if the database crashes between step 3 and step 5. When the server/service recovers, it will be processed again.
If the processing step only computes results which are sent to the database in the same connection as the queuing queries, then no one will be able to see that it was processed twice, as the results of the first time were never visible.
However if the processing step talks to the outside world, such as sending an email or charging a credit card, that action will be taken twice and both will be visible. The only way to avoid that is to use two-phase commits for all dealings with the outside world. Also, if the worker keeps two connections to the database and is not disciplined about their use, then that can also lead to visible double-processing.
Question 2
For your second question, there are several ways it can be made cleaner.
Most importantly, you will want to change the advisory lock from session-duration to transaction-duration. If you leave it at session-duration, long-lived workers will be become slower and slower and will use more and more memory as time goes on. This is safe to do, because in the query as written you are checking the processed flag in both the sub-select and in the update itself.
You could make the table structure itself cleaner. You could have one table with both the processed flag and the results field, instead of two tables. Or if you want two tables, you could remove the processed flag from the job table and signify completion simply be deleting the completed record from the table, rather than updating the processed flag.
Assuming you don't want to make such changes, you could still clean up the SQL without changing the table structure or semantics. You do need to lock the tuple to avoid a race condition with the release of the advisory lock. But rather than using the degenerate id=id construct (which some future maintainer is likely to remove, because it is not intuitively obvious why it is even there), you might as well just set the tuple to its final state by setting processed=true, and then removing that second update step from your step 4. This is safe to do because you do not issue an intermediate commit, so no one can see the tuple in this intermediate state of having processed=true but not yet really being processed.
UPDATE job
SET processed = true
WHERE id =
(
SELECT MIN(id)
FROM job
WHERE processed = false AND pg_try_advisory_xact_lock(id) = true
)
AND processed = false
RETURNING id
However, this query still has the unwanted feature that often someone looking for the next job to process will find no rows. That is because it suffered a race condition which was then filtered out by the outer processed=false condition. This is OK as long as your workers are prepared to retry, but it leads to needless contention in the database. This can be improved by making the inner select lock the tuple when it first encounters it by switching from a min(id) to a LIMIT 1 query:
UPDATE job
SET processed=true
WHERE id =
(
SELECT id
FROM job
WHERE processed = false AND pg_try_advisory_xact_lock(id) = true
order by id limit 1 for update
)
RETURNING id
If PostgreSQL allowed ORDER BY and LIMIT on UPDATES, then you could avoid the subselect altogether, but that is currently implemented (maybe it will be in 9.5).
For good performance (or even to avoid memory errors), you will need an index like:
create index on job (id) where processed = false;

Enforce Atomic Operations x Locks

I have a database model that works similar to a banking account (one table for operations, a nd a trigger to update the balance). I'm currently using SQL SERVER 2008 R2.
TABLE OPERATIONS
----------------
VL_CREDIT decimal(10,2)
VL_DEBIT decimal(10,2)
TABLE BALANCE
-------------
DT_OPERATION datetime
VL_CURRENT decimal(10,2)
PROCEDURE INSERT_OPERATION
--------------------------
GET LAST BALANCE BY DATE
CHECK IF VALUE OF OPERATION > BALANCE
IF > RETURN ERROR
ELSE INSERT INTO OPERATION(...,....)
The issue I have is the following:
The procedure to insert the operation has to check the balance to see if there's money available before inserting the operation, so the balance never gets negative. If there's no balance, I return some code to tell the user the balance is not enough.
My concern is: If this procedure gets called multiple times in a row, how can I guarantee that it's atomic?
I have some ideas, but as I am not sure which would guarantee it:
BEGIN TRANSACTION on the OPERATION PROCEDURE
Some sort of lock on selecting the BALANCE table, but it must hold until the end of procedure execution
Can you suggest some approach to guarantee that? Thanks in advance.
UPDATE
I read on MSDN (http://technet.microsoft.com/en-us/library/ms187373.aspx) that if my procedure has BEGIN/END TRANSACTION, and the SELECT on table BALANCE has WITH(TABLOCKX), it locks the table until the end of the transaction, so if a subsequent call to this procedure is made during the execution of the first, it will wait, and then guarantee that the value is always the last updated. Will it work? And if so, is it the best practice?
If you're amenable to changing your table structures, I'd build it this way:
create table Transactions (
SequenceNo int not null,
OpeningBalance decimal(38,4) not null,
Amount decimal(38,4) not null,
ClosingBalance as CONVERT(decimal(38,4),OpeningBalance + Amount) persisted,
PrevSequenceNo as CASE WHEN SequenceNo > 1 THEN SequenceNo - 1 END persisted,
constraint CK_Transaction_Sequence CHECK (SequenceNo > 0),
constraint PK_Transaction_Sequence PRIMARY KEY (SequenceNo),
constraint CK_Transaction_NotNegative CHECK (OpeningBalance + Amount >= 0),
constraint UQ_Transaction_BalanceCheck UNIQUE (SequenceNo, ClosingBalance),
constraint FK_Transaction_BalanceCheck FOREIGN KEY
(PrevSequenceNo, OpeningBalance)
references Transactions
(SequenceNo,ClosingBalance)
/* Optional - another check that Transaction 1 has 0 amount and
0 opening balance, if required */
)
Where you just apply credits and debits as +ve or -ve values for Amount. The above structure is enough to enforce the "not going negative" requirement (via CK_Transaction_NotNegative), and it also ensures that you know the current balance (by finding the row with the highest SequenceNo and taking the ClosingBalance value. Together, UQ_Transaction_BalanceCheck and FK_Transaction_BalanceCheck (and the computed columns) ensure that the entire sequence of transactions is valid, and PK_Transaction_Sequence keeps everything building in order
So, if we populate it with some data:
insert into Transactions (SequenceNo,OpeningBalance,Amount) values
(1,0.0,10.0),
(2,10.0,-5.50),
(3,4.50,2.75)
And now we can attempt an insert (this could be INSERT_PROCEDURE with #NewAmount passed as a parameter):
declare #NewAmount decimal(38,4)
set #NewAmount = -15.50
;With LastTransaction as (
select SequenceNo,ClosingBalance,
ROW_NUMBER() OVER (ORDER BY SequenceNo desc) as rn
from Transactions
)
insert into Transactions (SequenceNo,OpeningBalance,Amount)
select SequenceNo + 1, ClosingBalance, #NewAmount
from LastTransaction
where rn = 1
This insert fails because it would have caused the balance to go negative. But if #NewAmount was small enough, it would have succeeded. And if two inserts are attempted at "the same time" then either a) They're just far enough apart in reality that they both succeed, and the balances are all kept correct, or b) One of them will receive a PK violation error.

SQLite - a smart way to remove and add new objects

I have a table in my database and I want for each row in my table to have an unique id and to have the rows named sequently.
For example: I have 10 rows, each has an id - starting from 0, ending at 9. When I remove a row from a table, lets say - row number 5, there occurs a "hole". And afterwards I add more data, but the "hole" is still there.
It is important for me to know exact number of rows and to have at every row data in order to access my table arbitrarily.
There is a way in sqlite to do it? Or do I have to manually manage removing and adding of data?
Thank you in advance,
Ilya.
It may be worth considering whether you really want to do this. Primary keys usually should not change through the lifetime of the row, and you can always find the total number of rows by running:
SELECT COUNT(*) FROM table_name;
That said, the following trigger should "roll down" every ID number whenever a delete creates a hole:
CREATE TRIGGER sequentialize_ids AFTER DELETE ON table_name FOR EACH ROW
BEGIN
UPDATE table_name SET id=id-1 WHERE id > OLD.id;
END;
I tested this on a sample database and it appears to work as advertised. If you have the following table:
id name
1 First
2 Second
3 Third
4 Fourth
And delete where id=2, afterwards the table will be:
id name
1 First
2 Third
3 Fourth
This trigger can take a long time and has very poor scaling properties (it takes longer for each row you delete and each remaining row in the table). On my computer, deleting 15 rows at the beginning of a 1000 row table took 0.26 seconds, but this will certainly be longer on an iPhone.
I strongly suggest that you re-think your design. In my opinion your asking yourself for troubles in the future (e.g. if you create another table and want to have some relations between the tables).
If you want to know the number of rows just use:
SELECT count(*) FROM table_name;
If you want to access rows in the order of id, just define this field using PRIMARY KEY constraint:
CREATE TABLE test (
id INTEGER PRIMARY KEY,
...
);
and get rows using ORDER BY clause with ASC or DESC:
SELECT * FROM table_name ORDER BY id ASC;
Sqlite creates an index for the primary key field, so this query is fast.
I think that you would be interested in reading about LIMIT and OFFSET clauses.
The best source of information is the SQLite documentation.
If you don't want to take Stephen Jennings's very clever but performance-killing approach, just query a little differently. Instead of:
SELECT * FROM mytable WHERE id = ?
Do:
SELECT * FROM mytable ORDER BY id LIMIT 1 OFFSET ?
Note that OFFSET is zero-based, so you may need to subtract 1 from the variable you're indexing in with.
If you want to reclaim deleted row ids the VACUUM command or pragma may be what you seek,
http://www.sqlite.org/faq.html#q12
http://www.sqlite.org/lang_vacuum.html
http://www.sqlite.org/pragma.html#pragma_auto_vacuum