June 2018 - 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

Dear Professor/Lecturer Please excuse us for contacting you directly. We are offering an efficient service to help you ensure your academic and professional work is written in perfect English. We will check the grammar and style of your work and return it to you to meet your requirements and deadlines. Proof-Reading-Service.com can provide you with a professional proofreading service at a very reasonable rate. All our proofreaders are highly qualified native English speakers. Many work as leading academics in their fields and all have extensive experience of proofreading to the highest standards. If you are interested in our service, please take a look at our website: www.proof-reading-service.com All you have to do is send us your document as a word attachment with the deadline and we will guarantee delivery of a perfectly written document to give you complete confidence when you submit your work. The fee is worked out on a flat rate (£6.95 per thousand words or 0.695 pence per word), so you know exactly how much the proofreading will cost in advance. Once we have received your document(s) we will confirm the word count, the price and the deadline. If you have not heard from us within 2 hours during normal business hours after you have sent your work please resend it from a different email account or send the file to proofreadings(a)gmail.com. We look forward to hearing from you! Yours faithfully Proof-Reading-Service.com

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GDK reported error. MT_mremap: mremap failed. !OS: Cannot allocate memory
by RanchoYuan 04 Jul '19

04 Jul '19

Hi Stefan, Thanks for your reply! We have run the query a few times with different size of data. There we used 16G RAM(actually 13.5G was used), and find the size of 10G's data is the critical point that can run the query. All of the data files' size are listed below, each file name is a table name(there are only a few tables are refered -- store_sales, date_dim, item, customer, catalog_sales, web_sales): 7.4K call_center.dat 1.6M catalog_page.dat 212M catalog_returns.dat 2.9G catalog_sales.dat 27M customer_address.dat 64M customer.dat 77M customer_demographics.dat 9.9M date_dim.dat 77B dbgen_version.dat 149K household_demographics.dat 328B income_band.dat 2.6G inventory.dat 28M item.dat 61K promotion.dat 1.7K reason.dat 1.1K ship_mode.dat 27K store.dat 323M store_returns.dat 3.8G store_sales.dat 4.9M time_dim.dat 1.2K warehouse.dat 19K web_page.dat 98M web_returns.dat 1.5G web_sales.dat 12K web_site.dat So we guess that the monetdb has no memory management? For the output of `mserver5 --version` is: MonetDB 5 server v11.27.13 "Jul2017-SP4" (64-bit, 128-bit integers) Copyright (c) 1993 - July 2008 CWI Copyright (c) August 2008 - 2018 MonetDB B.V., all rights reserved Visit https://www.monetdb.org/ for further information Found 17.0GiB available memory, 40 available cpu cores Libraries: libpcre: 8.38 2015-11-23 (compiled with 8.38) openssl: OpenSSL 1.0.2g 1 Mar 2016 (compiled with OpenSSL 1.0.2g 1 Mar 2016) libxml2: 2.9.3 (compiled with 2.9.3) Compiled by: monetdb(a)MonetDB-0.0 (x86_64-pc-linux-gnu) Compilation: gcc -g -O2 Linking : /usr/bin/ld -m elf_x86_64 And the size of processes is not limited. To let you reproduce the problem conveniently, I'll provide more details here: you can get tpc-ds from its website(we use version 2.6.0). Install the tpc-ds, access the directory v2.6.0/tools and run `./dsdgen -scale 10 -dir /home/monetdb/tpc-ds_test_data10G` to generate the data. When data has been generated, using the script /expe.sh/ to create tables and load the data. The query script is 123.tpcds.23.sql.(The syntaxs of other queries that tpc-ds generates is not suitable for monetdb all, we don't modify them all when the problem occurred). One more question, I can't get your reply email, so I don't know how to reply you, for this case, I could only send a new mail echo time. Thanks! Regards, Rancho

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Memory management, 8 years later
by Roberto Cornacchia 28 Jun '18

28 Jun '18

Hi all, 8 yeas after this interesting thread about using ulimit to limit the data segment size ( https://www.monetdb.org/pipermail/users-list/2010-March/004007.html) a few things have changed and I find myself a bit lost again about memory management. At some point (can't remember when) mserver5 stopped respecting ulimit. No matter how I change the limits, it always sees all available physical ram. Does any other mechanism exist? The issue I'm facing all the time, and for which I find very little documentation, is: - multiple dbfarms, possibly tens of mserver5 instances, running on the same (virtual) machine, plus other applications - Not necessarily, but most times each dmfarm is served by a Docker container - CPU and memory resources need to be share fairly (ideally, controlling priorities) - No mserver5 should ever be killed because of memory issues Now, especially when using Docker, there are means to control the maximum memory size allowed to each process. However, the resolution in case of overusage is to kill the process. That is of course not a solution. What I'm looking for is: can I set a cap to resources *at process level*, in a way that mserver5 will just *see* those, make the best out of them, and never try to use more? (yes, one way would be a VM, but far from ideal for me) Does anyone have experience with / tips about multi-dbfarm environments? Thanks! Roberto

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Troublesome Query
by Doherty, Adam 23 Jun '18

23 Jun '18

Hi all: I'm trying to figure how to calculate the time delta between two events. My events have a timestamp, event source, event type, and an event state and event id. So an event looks like - event_date_time event_source event_type event_state event_id 2018-06-22 09:05:07.000000 MODULE123 TYPEABC ACK 24567890 2018-06-22 11:32:14.000000 MODULE123 TYPEABC UNACK 24812266 This makes up a unique "event", start to finish. However I have hundreds or thousands of entries between and I want be able to group them together in their unique pairings as above. I'm not sure how to wrap my head around this one. Adam Doherty

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Performance issues when streaming records from table.
by Manuel Pagliai 20 Jun '18

20 Jun '18

We are interested in adding support to import records from Monetdb tables in the ETL we are developing. We have performance issues when executing queries like: select col0, col1, ... coln from <table> on tables with a large number of records. What I am concerned about is the time spent upfront, before the first record is retrieved: once records become available we can start processing them. For example, on my machine, executing a executing a select * from <table> query on a 68 million records table takes around 24 seconds for the query to execute, before it is actually possible to start retrieving records from the server response. Queries are submitted via the JDBC driver. Is there a more efficient way of streaming records from a table ? Thanks, Best regards, *Manuel Pagliai* Visokio Ltd www.visokio.com +44 20 7351 4646

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Announcement: New Mar2018-SP1 Bugfix release of MonetDB suite
by Panagiotis Koutsourakis 20 Jun '18

20 Jun '18

The MonetDB team at CWI/MonetDB BV is pleased to announce the Mar2018-SP1 bugfix release of the MonetDB suite of programs. More information about MonetDB can be found on our website at <https://www.monetdb.org/>. For details on this release, please see the release notes at <https://www.monetdb.org/Downloads/ReleaseNotes>. As usual, the download location is <https://dev.monetdb.org/downloads/>. Mar 2018-SP1 bugfix release (11.29.7) Build Environment * On Linux and Unix, try not to link to libraries multiple times: that only causes the code (and worse, the variables in those libraries) to be included multiple times. On Windows, we do need to link to libraries multiple times (once for each DLL we create if the DLL references anything from the library) but that doesn't cause the linked library to be loaded multiple times. SQL Frontend * Corrected the definition of view: sys.ids. Bug Fixes * 6562: Sqlitelogictest crash on group by query with not in operator * 6565: Sqlitelogictest crash on complex select query with coalesce call * 6566: Sqlitelogictest unavailable calc.- MAL operations * 6568: Sqlitelogictest crash on complex case query * 6569: Sqlitelogictest select query with not between cause with wrong results * 6570: Sqlitelogictest select coalesce undefined calc * 6572: ordered index Error in optimizer garbageCollector * 6573: Sqlitelogictest crash on complex select query with case statement * 6574: server crashed could not find ordered index while creating a table * 6576: Sqlitelogictest aritmetic expressions with negative numbers handling * 6577: creating temp table kills performance of the original query * 6578: One two-tuple insert gives different results than two single inserts * 6581: Join condition errors. * 6583: Fixed size string concatenation with integer results in fixed size string of size 0 * 6584: SELECT FROM REMOTE TABLE WHERE IS NOT NULL produces wrong result * 6585: Nested Merge tables cause an infinite loop in rel_optimizer * 6587: Sqlitelogictest crash on complex case statement * 6589: Sqlitelogictest crash on complex on complex expression * 6594: Sqlitelogictest crash on complex case statement * 6595: Remote decimal division triggers assertion / returns wrong answer * 6598: Python 3.4 not supported (due to usage of Py_DecodeLocale) * 6600: Sqlitelogictest queries fail to execute * 6601: "where is null" clause on remote table causes problem with next query * 6602: Sqlitelogictest wrong results in IN query * 6603: Sqlitelogictest: Aggregation query with distinct clause produces duplicated rows

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pymonetdb or Python UDF
by Doherty, Adam 17 Jun '18

17 Jun '18

Hello all: This is more of curiosity but I have data in my events table currently trapped in a nvarchar field. I am wondering if I can build a table and do execute a select into with a python UDF pulling data from the existing fields plus the values of my nvarchar field. My string data has the following format - "key1=value, key2=val, key3=value"... I want to break out the data first by splitting on the , and then the = Keys would be the columns in the table. I can do this with a python script and pymonetdb but a UDF would be faster. Adam Doherty Process Control Systems Administrator Kearl Technical, Imperial 505 Quarry Park Blvd SE W3B.224 Calgary, AB T2C 5N1 adam.doherty(a)esso.ca<mailto:adam.doherty@esso.ca> P 587.476.4640<tel:+15874764640> M 403.869.1636<tel:+14038691636> imperialoil.ca<http://www.imperialoil.ca/Canada-English/default.aspx> | Twitter<http://www.twitter.com/imperialoil> | YouTube<http://www.youtube.com/imperialoil>

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