November 2016 - users-list

[MonetDB-users] Books CDs
by CHARTS LICENSING 11 Aug '24

11 Aug '24

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Multi-column update based on joined table
by Lee Hachadoorian 11 Aug '24

11 Aug '24

I need to update multiple columns (~250) from one table to another based on a two-column key. In Postgres I would write this using the FROM clause, but since MonetDB doesn't support the FROM clause, I've successfully updated one column with: UPDATE census.acs2010_5yr SET b07401001 = ( SELECT CAST(b07401001 AS int) FROM acs2010_5yr.tmp_seq0001 WHERE acs2010_5yr.stusab = tmp_seq0001.stusab AND acs2010_5yr.logrecno = tmp_seq0001.logrecno ); My question is whether there is any benefit to writing a multiple column update into a single UPDATE statement: UPDATE target_table SET column1 = (SELECT column1 FROM source_table WHERE target_table.key = source_table.key), column2 = (SELECT column2 FROM source_table WHERE target_table.key = source_table.key), ..., columnN = (SELECT columnN FROM source_table WHERE target_table.key = source_table.key); On Postgres I believe the multi-column update using a table join would only have to do the sequential scan of each table once, but with the necessity of sub-selects in MonetDB, what is the backend doing? Is it already doing an index scan once for each row in the single column case, then doing it once for each row * column in the multi-column case? Best, --Lee -- Lee Hachadoorian Asst Professor of Geography, Dartmouth College http://freecity.commons.gc.cuny.edu/

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[MonetDB-users] XQuery API and XLink/XUpdate support
by Alexandra Mart�nez 27 Jun '24

27 Jun '24

Hello all, I was wondering if there is any documentation about the API for XQuery (i.e., how to write xqueries from a Java program). Also, I am interested in using some features of XLink and XUpdate on top of my XML database. Is support for any of these in progress? Thanks in advance, Alexandra ______________________________________________________ Click here to donate to the Hurricane Katrina relief effort. http://store.yahoo.com/redcross-donate3/

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[MonetDB-users] Proofreading your professional documents
by Richard Hounslow 24 Feb '24

24 Feb '24

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Remote Table IS NULL
by Siklós Gábor 27 Mar '17

27 Mar '17

Hi there, We have an issue about the remote table on monetdb version of 2016 (sp1 and sp2) on Ubuntu 14.04 and on Windows Server2012 R2 The scenario for reproducing the issue with two nodes on node1 Create a table on remote node and fill it: CREATE TABLE test(id int not null, name text, valid boolean); INSERT INTO test (id, name) VALUES (1, '1'); INSERT INTO test (id, name) VALUES (2, '2'); INSERT INTO test (id) VALUES (3); on node2 CREATE REMOTE TABLE test(id int not null, name text, valid boolean) ON 'mapi:monetdb://node1:50000/dbfarm'; Then on node2: select * from test; +------+------+-------+ | id | name | valid | +======+======+=======+ | 1 | 1 | null | | 2 | 2 | null | | 3 | null | null | +------+------+-------+ It works fine, but: select * from test where name is null; +----+------+-------+ | id | name | valid | +====+======+=======+ +----+------+-------+ id 3 should appear here. Furthermore: select * from test where name is not null; (mapi:monetdb://monetdb@192.168.254.31/reports2) Cannot register project ( select ( table(sys.test) [ test.id NOT NULL, test.name, test.valid ] COUNT ) [ clob "NULL" ! <= test.name ! <= clob "NULL" ] ) [ test.id NOT NULL, test.name, test.valid ] REMOTE mapi:monetdb://.../... select * from test where valid is null; illegal input, not a JSON header (got '') and node1 is crashed (need : monetdb start farm). After downgrading on ubuntu 14.04 to version of 2015 (SP4) this scenraio works fine. Thanks, SG

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Python Aggregate functions
by Anderson, David B 06 Feb '17

06 Feb '17

Mark, I think there is a bug in the implementation of the PYTHON_MAP aggregate functions. The return value of a PYTHON_MAP aggregate function can change if there are other functions in the query. The return value of my function weighted_percentile_0 (definition below) changes if I include the function median() in my query. The results are incorrect if median() isn't in the query, but are correct if median() is in the query. In this test case, the weights (v2) are all 1 and the values (v1) are uniformly sampled integers from [1,10]. Number of rows for each fctr is ~1000, and my function should reduce to min(v1) in this case. Is some information bleeding between threads? Should I submit a bug report? This is on the default branch. Thanks, Dave sql>select fctr,weighted_percentile_0(v1,v2),min(v1) from mini where fctr < 10 group by fctr order by fctr; +------+--------------------------+------+ | fctr | L1 | L2 | +======+==========================+======+ | 1 | 3 | 1 | | 2 | 2 | 1 | | 3 | 2 | 1 | | 4 | 1 | 1 | | 5 | 3 | 1 | | 6 | 3 | 1 | | 7 | 2 | 1 | | 8 | 1 | 1 | | 9 | 2 | 1 | +------+--------------------------+------+ 9 tuples (126.928ms) sql>select fctr,weighted_percentile_0(v1,v2),min(v1),median(v1) from mini where fctr < 10 group by fctr order by fctr; +------+--------------------------+------+------+ | fctr | L1 | L2 | L3 | +======+==========================+======+======+ | 1 | 1 | 1 | 5 | | 2 | 1 | 1 | 5 | | 3 | 1 | 1 | 5 | | 4 | 1 | 1 | 5 | | 5 | 1 | 1 | 5 | | 6 | 1 | 1 | 5 | | 7 | 1 | 1 | 5 | | 8 | 1 | 1 | 5 | | 9 | 1 | 1 | 5 | +------+--------------------------+------+------+ 9 tuples (519.195ms) sql> CREATE AGGREGATE weighted_percentile_0(a DOUBLE, w DOUBLE) RETURNS DOUBLE LANGUAGE PYTHON_MAP { import numpy as np # Standardize and sort based on values in a q = np.array([0]) / 100.0 idx = np.argsort(a) a_sort = a[idx] w_sort = w[idx] # Get the cumulative sum of weights ecdf = np.cumsum(w_sort) # Find the percentile index positions associated with the percentiles p = q * (w_sort.sum() - 1) # Find the bounding indices (both low and high) idx_low = np.searchsorted(ecdf, p, side='right') idx_high = np.searchsorted(ecdf, p + 1, side='right') idx_high[idx_high > ecdf.size - 1] = ecdf.size - 1 # Calculate the weights weights_high = p - np.floor(p) weights_low = 1.0 - weights_high # Extract the low/high indexes and multiply by the corresponding weights x1 = np.take(a_sort, idx_low) * weights_low x2 = np.take(a_sort, idx_high) * weights_high wp = np.add(x1,x2) return(wp[0]) };

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SUM() OVER (ORDER BY..)
by Anthony Damico 13 Dec '16

13 Dec '16

hi, monetdb does not support SUM() OVER commands.. does anyone have a smart alternative to implement this? thanks SELECT batch_id, job_count, SUM(job_count) OVER (ORDER BY duration) as cumjobs, SUM(job_count) over () as totjobs, duration FROM test_data ;

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Building monetdb with Python 3
by Joseph D'silva 01 Dec '16

01 Dec '16

Hi all, Has anyone had any luck building the sources with Python 3 ? I tried building the Dec2016 branch from git, passing --with-python3=/usr/bin/python3 --with-pyversion=/usr/bin/python3 --with-pyconfig=/usr/bin/python3-config to configure, but received many errors during make under the pyapi directory, such as. /usr/include/python3.5m/object.h:86:5: error: missing braces around initializer [-Werror=missing-braces] { _PyObject_EXTRA_INIT \ ^ connection.c:159:5: note: in expansion of macro ‘PyObject_HEAD_INIT’ PyObject_HEAD_INIT(NULL) ^ /usr/include/python3.5m/object.h:86:5: note: (near initialization for ‘Py_ConnectionType.ob_base’) { _PyObject_EXTRA_INIT \ ^ connection.c:159:5: note: in expansion of macro ‘PyObject_HEAD_INIT’ PyObject_HEAD_INIT(NULL) ^ connection.c:159:5: error: missing initializer for field ‘ob_size’ of ‘PyVarObject {aka struct <anonymous>}’ [-Werror=missing-field-initializers] ................. connection.c:246:5: error: ‘return’ with a value, in function returning void [-Werror] import_array(); ^ It looks like some of the macro definitions to make python3 header files work with the pyapi source might be missing. I tried fixing some of the sources like unicode.c, formatinput.c etc. But it looks like majority of the source files have issues. Thanks, Joseph

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MonetDB and IN search
by blacky_2k2＠yahoo.com 29 Nov '16

29 Nov '16

Hello, We’ve been battling for some time with what is fundamentally a simple query. We have a databases with about 15 columns which store int and float values. The query searches in each column with an IN condition , where the possible test values in the IN condition may vary from a 1 to 200 - where these 200 conditions are all the possible values of that column. So normally a query would look something like: SELECT id FROM table WHERE a IN (1,2,3,4) AND b IN (4,5,6,) AND c IN (2,5,6) ...... AND i = 5 etc. The database has about 2 mil rows but will grow to potentially 10 mil rows. A query similar to the one above takes about 80-100 ms. With about 50 test values for each IN. So far, the best results we got with MariaDB and proper indexing using Engine Memory where the above query takes about 2ms. We suspect MonetDB is not optimised for such queries, but since we don’t know much about its workings can you please confirm this? Otherwise, is there a way to improve the above query? Say using multiple JOINs instead of IN ? By the way, we are experimenting with MonetDB out of curiosity, we heard a lot of good things about it. Thank you very much, Silviu

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Improved concurrency version of MonetDB
by Puthick Hok 24 Nov '16

24 Nov '16

Hi, I'm using MonetDB v11.23.13 (Jun2016-SP2). We decided to use MonetDB to store DNA marker data for our plant breeding platform (www.kddart.org) 2 years ago based on MonetDB performance on data retrieval and data update is also good. The use of MonetDB is not purely OLAP. There are lot of aspects of OLTP because people need to load marker data from their genotyping services. We finish integrating MonetDB into the platform and developing more tools for the system. As the platform is getting more mature, we started to do concurrency testing against the system including the part that is relying on MonetDB. Naively, I ran into a concurrency problem described in a master thesis by Rene Tassy (Improving Transactional Scalability in MonetDB). The work done in the thesis is very promising and I would like to thank you all for that. My question in relation to how I would deal with my problem is that what is the time frame for the improved MVCC Optimistic Concurrency Strategy in the MonetDB release? Regards, Puthick

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