June 2018 - users-list

joinable generate_series with arguments from a table
by Stefan de Konink 14 Jun '18

14 Jun '18

Goodmorning, At this moment there is no functional compatibility between the PostgreSQL and MonetDB with respect to the generate_series function. The range in PostgreSQL is inclusive, in MonetDB exclusive. More importantly generate_series can't be used with argument that is joined from a different table, MonetDB just seems to support a subquery, hence joining that back without a primary is impossible. PostgreSQL; select generate_series(a, b), a from (select 1 as a, 2 as b) as a; generate_series | a -----------------+--- 1 | 1 2 | 1 (2 rows) MonetDB; select * from generate_series((select 1 as a, 2 as b)); +-------+ | value | +=======+ | 1 | +-------+ If I would like to functionally achieve the following; I have list that states the speeds over partial segments, identified by linear referencing. From 10 meter to 12 meter, the distance was 2 meter and speed was 2s. 10 2 2 I would like to expand these values to segments of one meter, hence end up with a table that would state: 10 2 2 11 2 2 12 2 2 Now I am aware of the Python bindings and I could achieve what I wanted by the function below, but I would find generate_series still very practical. DROP FUNCTION expand_per_meter; CREATE FUNCTION expand_per_meter(trip_hash BIGINT, userstopcode STRING, distancesincelastuserstop INTEGER, s INTEGER, t INTEGER) RETURNS TABLE(trip_hash BIGINT, userstopcode STRING, distancesincelastuserstop INTEGER, s INTEGER, t INTEGER) LANGUAGE PYTHON { result = dict() result['trip_hash'] = [] result['userstopcode'] = [] result['distancesincelastuserstop'] = [] result['s'] = [] result['t'] = [] for i in range(0, len(trip_hash)): expanded = range(distancesincelastuserstop[i], distancesincelastuserstop[i] + s[i] + 1) expand = len(expanded) result['trip_hash'] += [trip_hash[i]] * expand result['userstopcode'] += [userstopcode[i]] * expand result['distancesincelastuserstop'] += expanded result['s'] += [s[i]] * expand result['t'] += [t[i]] * expand return result }; -- Stefan

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Re: Combine a table-returning function with the source table
by Mark Clements 13 Jun '18

13 Jun '18

Stefan, This is a good question. For the specific example, you are quite correct. However, the motivation for the question came from using the MonetDB-rmath extension and embedded R: often it is more efficient to calculate a number of values (e.g. the confidence intervals and p-values) together and then return all of the values as a table. This probably also reflects that I am a statistician and an old R user. The recent article by Raasveldt suggested that analysis objects from Python could be stored natively rather than being serialised BLOBs. This could be further extended to storing R objects natively. Members of the objects could then be extracted as they are needed. Admittedly, this would lose many relational advantages. My suggestion is halfway, where R and Python can be used for analytics, with simple relational storage of the results. Actually, is there any way to optimise a lateral call using BATs? -- Mark On 13 Jun 2018 17:43, Stefan Manegold <Stefan.Manegold(a)cwi.nl> wrote: Hi Mark, just out of curiosity, (in the given case/example) what's wrong with a simple select *, mean-1.96*sd as lci, mean+1.96*sd as uci from test; or create or replace function ci(se double) returns double begin return 1.96*se; end; select *, mean-ci(sd) as lci, mean+ci(sd) as uci from test; in case you really want/need to avoid the "redundant" occurrence or "1.96" ... Thanks! Best, Stefan ----- On Jun 13, 2018, at 5:30 PM, Mark Clements mark.clements(a)ki.se wrote: > Jennie, > > Thank you for replying to this inquiry - it's appreciated. > > Your solution gives the right result - but it requires changing the > function call and will not generalise easily to other column types or > other number of covariates. If we had another table such as: > > drop table test; > create table test as select 1 as id, 2 as sex, cast(3 as double) as > mean, cast(4.0 as double) as sd; > -- and repeating the function > create or replace function cis(mu double, se double) returns table(lci > double, uci double) > begin return select mu-1.96*se, mu+1.96*se; > end; > > we can get all of the test table combined with the confidence interval by: > > -- row_number() > select * from > (select *, row_number() over() as rid from test) as t1 > natural join > (select *, row_number() over() as rid from cis((select mean,sd from > test))) as t2; > -- or using lateral > select * from test, lateral cis(test.mean,test.sd); > > The row_number solution is fast, and the lateral solution is simple. I > was hoping for: > > select *, cis(mean,test).* from test; > > Again, thank you for your help. > > -- Mark > > On 06/08/2018 01:53 PM, Ying Zhang wrote: >> Hai Mark, >> >> I’m just wonder if this gives you wat you want: >> >> create function cis(mu double, se double) >> returns table(mu_out double, lci double, uci double) >> begin >> return select mu, mu-1.96*se, mu+1.96*se; >> end; >> >> Regards, >> Jennie > > _______________________________________________ > users-list mailing list > users-list(a)monetdb.org > https://www.monetdb.org/mailman/listinfo/users-list -- | Stefan.Manegold(a)CWI.nl | DB Architectures (DA) | | www.CWI.nl/~manegold/<http://www.CWI.nl/~manegold/> | Science Park 123 (L321) | | +31 (0)20 592-4212 | 1098 XG Amsterdam (NL) | _______________________________________________ users-list mailing list users-list(a)monetdb.org https://www.monetdb.org/mailman/listinfo/users-list

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Combine a table-returning function with the source table
by Mark Clements 13 Jun '18

13 Jun '18

For using the MonetDB-rmath extension, I was interested in using table-returning functions to return multiple values. Is there a fast and elegant way to combine the results with the source table in SQL? To make this concrete, consider some test data and a function to calculate a 95% confidence interval from a mean and standard error: drop table test; create table test as select cast(value as double) as value from generate_series(0,5); drop function cis(double,double); create function cis(mu double, se double) returns table(lci double, uci double) begin return select mu-1.96*se, mu+1.96*se; end; We can then call the table-returning function: select * from cis((select value, 1.0 from test)); If we want to re-join the results with the source table, we could use row_number() or use lateral: -- Using row_number: select * from (select *, row_number() over() as rid from test) as t1 natural join (select *, row_number() over() as rid from cis((select value,1.0 from test))) as t2; -- Using lateral: select * from test, lateral cis(test.value, cast(1.0 as double)) as t2; I believe that the latter will lead to a slow loop, even when BAT functions are available. The table-returning function can be used in the select statement only for a scalar expression: select cis(0,1).*; -- ok select cis(0,1).* from test; -- Error: no such operator 'cis' select cis(value,1).* from test; -- Error: identifier 'value' unknown Again, is there a fast and elegant way to combine the source table with a table-returning function in SQL? Kindly, Mark.

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Temporal Function Issues
by Doherty, Adam 13 Jun '18

13 Jun '18

Hello all: I am trying to find the most efficient way to filter results for those matching today only. My events table has 550 million rows and I want a view as follows- CREATE VIEW events_today AS SELECT * FROM events WHERE str_to_date(timestamp_to_str(event_timestamp, '%Y-%m-%d'), '%Y-%m-%d') = CURRENT_DATE which should give me all events with today's date. Running the SELECT by itself also never returns. However, the query just hangs without ever returning. I'm running 11.29.3 (Mar2018) on CentOS 7 with 128GB and 16 Cores. Adam

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High Memory Usage - Sever Not Releasing Resources?
by Doherty, Adam 08 Jun '18

08 Jun '18

Hi all: I ran into an issue yesterday when I ran a simple group count query - The query took 7 minutes, 13 seconds to run. Query was as follows - SELECT zone, count(*) FROM chronicle.events WHERE event_type = 'mb' GROUP BY zone This table, which a merge table currently has 546 million events. The merge table is made up of currently two merge table each representing a year (events_2018, and events_2017). Those merge tables are each made up of four tables, events_year_zone_(1-4) I have a scheduled task which inserts events into the relevant tables every 5 minutes from 5 Microsoft SQL Servers. Roughly 12,000 events broken across 5 inserts (one for each server). The import process is handled with a C# Windows service that utilizes ODBC to talk to MonetDB. The server is currently MonetDB v11.27.11 (July2017-SP3) running on VMware 6.5 in a CentOS 7 VM with 64GB of RAM, and 16 CPU cores. When I ran into this issue yesterday, the mserver5 process was utilizing 90% of available RAM. This was making my insertion task take longer and longer each time, and simple queries like the one above took minutes. Logged into the server via SSH, the input lag as a result of the almost total resource usage caused me to reboot the server. I restarted the VM, and the same query took 20 seconds. I'd like to sort where this issue might be coming from, but I'm not sure where to look. This server is currently part of a proof-of-concept project that will soon be going to production. Any guidance is greatly appreciated. Adam

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ODBC Error on Insert
by Doherty, Adam 06 Jun '18

06 Jun '18

Hi All: I'm having some issues using ODBC with C#. I am trying to insert the contents of a DataTable into Monet using a foreach loop with MonetDB ODBC client under Windows. This is the error I receive... System.Data.Odbc.OdbcException (0x80131937): ERROR [42000] [MonetDB][ODBC Driver 11.27.11]syntax error, unexpected ',' in: "execute 5 (timestamp '2018-06-04 21:22:25',8651,'EVENT','','SYSTEM','1810_INFRA_" This is my loop which is wrapped in a transaction - foreach (DataRow row in events.Rows) { cmd.CommandText = String.Format("INSERT INTO chronicle.events_{0}_zone_{1} VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)", year, zone); cmd.Parameters.AddWithValue("@date_time", row["Date_Time"]); cmd.Parameters.AddWithValue("@fracsec", row["FracSec"]); cmd.Parameters.AddWithValue("@event_type", row["Event_Type"]); Truncated for brevity. I'm not sure where the error in my insert statement is because the error message itself appear to be truncated. Very frustrating as it hangs on the first row. Adam

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