How to tell if record has changed in Postgres - postgresql

I have a bit of an "upsert" type of question... but, I want to throw it out there because it's a little bit different than any that I've read on stackoverflow.
Basic problem.
I'm working on moving from mysql to PostgreSQL 9.1.5 (hosted on Heroku). As a part of that, I need to import multiple CSV files everyday. Some of the data is sales information and is almost guaranteed to be new and need to be inserted. But, other parts of the data is almost guaranteed to be the same. For example, the csv files (note plural) will have POS (point of sale) information in them. This rarely changes (and is most likely only via additions). Then there is product information. There are about 10,000 products (vast majority will be unchanged, but it's possible to have both additions and updates).
The final item (but is important), is that I have a requirement to be able to provide an audit trail/information for any given item. For example, if I add a new POS record, I need to be able to trace that back to the file it was found in. If I change a UPC code or description of a product, then I need to be able to trace it back to the import (and file) where the change came from.
Solution that I'm contemplating.
Since the data is provided to me via CSV, then I'm working around the idea that COPY will be the best/fastest way. The structure of the data in the files is not exactly what I have in the database (i.e. final destination). So, I'm copying them into tables in the staging schema that match the CSV (note: one schema per datasource). The tables in the staging schemas will have a before insert row triggers. These triggers can decide what to do with the data (insert, update or ignore).
For the tables that are most likely to contain new data, then it will try to insert first. If the record is already there, then it will return NULL (and stop the insert into the staging table). For tables that rarely change, then it will query the table and see if the record is found. If it is, then I need a way to see if any of the fields are changed. (because remember, I need to show that the record was modified by import x from file y) I obviously can just boiler plate out the code and test each column. But, was looking for something a little more "eloquent" and more maintainable than that.
In a way, what I'm kind of doing is combining a importing system with an audit trail system. So, in researching audit trails, I reviewed the following wiki.postgresql.org article. It seems like the hstore might be a nice way of getting changes (and being able to easily ignore some columns in the table that aren't important - e.g. "last_modified")
I'm about 90% sure it will all work... I've created some testing tables etc and played around with it.
My question?
Is a better, more maintainable way of accomplishing this task of finding the maybe 3 records out of 10K that require a change to the database. I could certainly write a python script (or something else) that reads the file and tries to figure out what to do with each record, but that feels horribly inefficient and will lead to lots of round trips.
A few final things:
I don't have control over the input files. I would love it if they only sent me the deltas, but they don't and it's completely outside of my control or influence.
he system is grow and new data sources are likely to be added that will greatly increase the amount of data being processed (so, I'm trying to keep things efficient)
I know this is not nice, simple SO question (like "how to sort a list in python") but I believe one of the great things about SO is that you can ask hard questions and people will share their thoughts about how they think the best way to solve it is.

I have lots of similar operations. What I do is COPY to temporary staging tables:
CREATE TEMP TABLE target_tmp AS
SELECT * FROM target_tbl LIMIT 0; -- only copy structure, no data
COPY target_tmp FROM '/path/to/target.csv';
For performance, run ANALYZE - temp. tables are not analyzed by autovacuum!
ANALYZE target_tmp;
Also for performance, maybe even create an index or two on the temp table, or add a primary key if the data allows for that.
ALTER TABLE ADD CONSTRAINT target_tmp_pkey PRIMARY KEY(target_id);
You don't need the performance stuff for small imports.
Then use the full scope of SQL commands to digest the new data.
For instance, if the primary key of the target table is target_id ..
Maybe DELETE what isn't there any more?
DELETE FROM target_tbl t
WHERE NOT EXISTS (
SELECT 1 FROM target_tmp t1
WHERE t1.target_id = t.target_id
);
Then UPDATE what's already there:
UPDATE target_tbl t
SET col1 = t1.col1
FROM target_tmp t1
WHERE t.target_id = t1.target_id
To avoid empty UPDATEs, simply add:
...
AND col1 IS DISTINCT FROM t1.col1; -- repeat for relevant columns
Or, if the whole row is relevant:
...
AND t IS DISTINCT FROM t1; -- check the whole row
Then INSERT what's new:
INSERT INTO target_tbl(target_id, col1)
SELECT t1.target_id, t1.col1
FROM target_tmp t1
LEFT JOIN target_tbl t USING (target_id)
WHERE t.target_id IS NULL;
Clean up if your session goes on (temp tables are dropped at end of session automatically):
DROP TABLE target_tmp;
Or use ON COMMIT DROP or similar with CREATE TEMP TABLE.
Code untested, but should work in any modern version of PostgreSQL except for typos.

Related

Statistics of all/many tables in FileMaker

I'm writing a kind of summary page for my FileMaker solution.
For this, I have define a "statistics" table, which uses formula fields with ExecuteSQL to gather info from most tables, such as number of records, recently changed records, etc.
This strangely takes a long time - around 10 seconds when I have a total of about 20k records in about 10 tables. The same SQL on any database system shouldn't take more than some fractions of a second.
What could the reason be, what can I do about it and where can I start debugging to figure out what's causing all this time?
The actual code is, like this:
SQLAusführen ( "SELECT COUNT(*) FROM " & _Stats::Table ; "" ; "" )
SQLAusführen ( "SELECT SUM(\"some_field_name\") FROM " & _Stats::Table ; "" ; "" )
Where "_Stats" is my statistics table, and it has a string field "Table" where I store the name of the other tables.
So each row in this _Stats table should have the stats for the table named in the "Table" field.
Update: I'm not using FileMaker server, this is a standalone client application.
We can definitely talk about why it may be slow. Usually this has mostly to do with the size and complexity of your schema. That is "usually", as you have found.
Can you instead use the DDR ( database design report ) instead? Much will depend on what you are actually doing with this data. Tools like FMPerception also will give you many of the stats you are looking for. Again, depends on what you are doing with it.
Also, can you post your actual calculation? Is the statistic table using unstored calculations? Is the statistics table related to any of the other tables? These are a couple things that will affect how ExecuteSQL performs.
One thing to keep in mind, whether ExecuteSQL, a Perform Find, or relationship, it's all the same basic query under-the-hood. So if it would be slow doing it one way, it's going to likely be slow with any other directly related approach.
Taking these one at a time:
All records count.
Placing an unstored calc in the target table allows you to get the count of the records through the relationship, without triggering a transfer of all records to the client. You can get the value from the first record in the relationship. Super light way to get that info vs using Count which requires FileMaker to touch every record on the other side.
Sum of Records Matching a Value.
using a field on the _Stats table with a relationship to the target table will reduce how much work FileMaker has to do to give you an answer.
Then having a Summary field in the target table so sum the records may prove to be more efficient than using an aggregate function. The summary field will also only sum the records that match the relationship. ( just don't show that field on any of your layouts if you don't need it )
ExecuteSQL is fastest when it can just rely on a simple index lookup. Once you get outside of that, it's primarily about testing to find the sweet-spot. Typically, I will use ExecuteSQL for retrieving either a JSON object from a user table, or verifying a single field value. Once you get into sorting and aggregate functions, you step outside of the optimizations of the function.
Also note, if you have an open record ( that means you as the current user ), FileMaker Server doesn't know what data you have on the client side, and so it sends ALL of the records. That's why I asked if you were using unstored calcs with ExecuteSQL. It can seem slow when you can't control when the calculations fire. Often I will put the updating of that data into a scheduled script.

Filling additional columns of an internal table with additional data by SELECT statement? Can this be done?

SELECT matnr ersda ernam laeda
FROM mara
INTO CORRESPONDING FIELDS OF TABLE gt_mara
UP TO 100 ROWS.
At this point I have 100 entries in the itab gt_mara.
SELECT aenam vpsta pstat lvorm mtart
FROM mara
INTO CORRESPONDING FIELDS OF TABLE gt_mara
FOR ALL ENTRIES IN gt_mara
WHERE matnr = gt_mara-matnr AND
ersda = gt_mara-ersda AND
ernam = gt_mara-ernam AND
laeda = gt_mara-laeda.
At this point I have 59 entries. Which makes sense. This code is buggy, because it might be modifying the selection criteria at run time.
Anyway what i intended was this: select the first 4 fields of the table at one point, and then select the other 5 at some other.
Of course, this is just an example. Perhaps the second select would be done on a different table with the same key or with a different number of fields.
So can this even be done?
Are there more efficient methods to achieve this than what comes to my mind by default (redoing the complete select) ?
Ok I think the essence of your question is more about whether you can update certain unfilled fields in an internal table directly through a second select statement.
The answer is no. Your second select statement would replace the contents in table gt_mara, so you would be left with an internal table where the first 4 fields are blank, and the last 5 are filled.
The best you could do is something like this:
SELECT matnr ersda ernam laeda
FROM mara
INTO CORRESPONDING FIELDS OF TABLE gt_mara
UP TO 100 ROWS.
SELECT matnr aenam vpsta pstat lvorm mtart
FROM mara
INTO CORRESPONDING FIELDS OF TABLE gt_mara2
FOR ALL ENTRIES IN gt_mara
WHERE matnr = gt_mara-matnr AND
ersda = gt_mara-ersda AND
ernam = gt_mara-ernam AND
laeda = gt_mara-laeda.
loop at gt_mara2 into ls_mara.
modify gt_mara from ls_mara transporting aenam vpsta pstat lvorm mtart
where matnr = ls_mara-matnr.
endloop.
This is obviously quite inefficient, which is why you would always try to make the database do as much of the work for you before you bring the data back to the application server. Obviously if the data is coming from the same table selecting it all in one go is going to be your best option. In most cases even if the data is in different tables you would be better off creating a view or using a join.
In rare cases it is necessary to loop at your internal table to fill in some fields that were not available to you when you did the original select.
Either SELECT everything you need right away (which is the preferred solution if the data comes from the same table) or SELECT the additional stuff later (which is a good idea if the stuff comes from a different table that is not used for the first selection). For assembling the result set, the database usually needs to access the entire dataset anyway, so it doesn't really hurt to select some additional fields - in contrast to hitting the database again with a massive SELECT statement (if the FOR ALL ENTRIES table gets large). Also bear in mind that - depending on the kind of processing you're doing - the contents of the table might have changed in the meantime. If the database transaction (LUW) ends (which is always the case between dialog steps), you loose the database-level transaction isolation.

Updating the text of a large number of stored procedures

The question pretty much sums it up. I've got to replace text in a large number for store procedures. Its not so many that doing it manually is impossible, but enough that I'm asking the question. I also prefer automation as it reduces the change of user error when we make the change in production.
I can Identify them like this:
select OBJECT_DEFINITION(object_id), *
from sys.procedures
where OBJECT_DEFINITION(object_id) like '%''MyExampleLiteral''%'
order by name
Is there any way to mass update them all to change 'MyExampleLiteral' to 'MyOtherExampleLiteral'?
I'd even settle for a way to open all the stored procs. Just Finding these store procs in a larger list will take some time.
I thought about generating alter statements using the above select statements, but then I lose line breaks.
Thanks in advance,
This is a Microsoft SQL Server.
There are different tools to use depending on the database in question. For example, Microsoft SQL Server Data Tools integrates with Visual Studio, and allows you to do these types of operations fairly easily. The database is stored in your solution as scripts, which you can then search and replace any keyword you wish. I'm assuming there would be similar tools available for other platforms.
You could do this with dynamic sql. Query the system tables to get all the SPs containing your "MyExampleLiteral":
SELECT [object_id] FROM sys.objects o
WHERE type_desc = 'SQL_STORED_PROCEDURE'
AND is_ms_shipped = 0
AND OBJECT_DEFINITION(o.[object_id]) LIKE '%<search string>%'
Then, write a while loop to go through those object_ids. In the while loop, get the OBJECT_DEFINITION() into a string and replace the "MyExampleLiteral", then replace CREATE PROCEDURE with ALTER PROCEDURE and execute the string using sp_executesql.
Doing something this crazy, make sure you backup the database first.

Efficient way of insert millions of rows, convert data and deal with it, on PostgreSQL+PostGIS

I have a big collection of data I want to use for user search later.
Currently I have 200 millions resources (~50GB). For each, I have latitude+longitude. The goal is to create spatial index to be able to do spatial queries on it.
So for that, the plan is to use PostgreSQL + PostGIS.
My data are on CSV file. I tried to use custom function to not insert duplicates, but after days of processing I gave up. I found a way to load it fast in the database: with COPY it takes less than 2 hours.
Then, I need to convert latitude+longitude on Geometry format. For that I just need to do:
ST_SetSRID(ST_MakePoint(longi::double precision,lat::double precision),4326))
After some checking, I saw that for 200 millions, I have 50 millions points. So, I think the best way is to have a table "TABLE_POINTS" that will store all the points, and a table "TABLE_RESOURCES" that will store resources with point_key.
So I need to fill "TABLE_POINTS" and "TABLE_RESOURCES" from temporary table "TABLE_TEMP" and not keeping duplicates.
For "POINTS" I did:
INSERT INTO TABLE_POINTS (point)
SELECT DISTINCT ST_SetSRID(ST_MakePoint(longi::double precision,lat::double precision),4326))
FROM TABLE_RESOURCES
I don't remember how much time it took, but I think it was matter of hours.
Then, to fill "RESOURCES", I tried:
INSERT INTO TABLE_RESOURCES (...,point_key)
SELECT DISTINCT ...,point_key
FROM TABLE_TEMP, TABLE_POINTS
WHERE ST_SetSRID(ST_MakePoint(longi::double precision,lat::double precision),4326) = point;
but again take days, and there is no way to see how far the query is ...
Also something important, the number of resources will continue to grow up, currently should be like 100K added by day, so storage should be optimized to keep fast access to data.
So if you have any idea for the loading or the optimization of the storage you are welcome.
Look into optimizing postgres first (ie google postgres unlogged, wal and fsync options), second do you really need points to be unique? Maybe just have one table with resources and points combined and not worry about duplicate points as it seems your duplicate lookup maybe whats slow.
For DISTINCT to work efficiently, you'll need a database index on those columns for which you want to eliminate duplicates (e.g. on the latitude/longitude columns, or even on the set of all columns).
So first insert all data into your temp table, then CREATE INDEX (this is usually faster that creating the index beforehand, as maintaining it during insertion is costly), and only afterwards do the INSERT INTO ... SELECT DISTINCT.
An EXPLAIN <your query> can tell you whether the SELECT DISTINCT now uses the index.

Apply diffs between two SQL Server Tables efficiently

I have a once-a-day ingestion case in which I will be getting a large file via FTP which contains the up-to-date versions of 4 database tables.
For each table, I would like to:
Truncate table in staging database
BCP the FTP'd file into that table
Find diffs (IUD) between staging table and production table
Make any required IUDs to production table so it matches staging table
I'm sure this is a reasonably common problem, but I'm not 100% sure as to the best way to approach it.
Are there any built in T-SQL features for this kind of problem, or do I just need to do various joins to find the inserted/updated/deleted records and execute them manually? I'm sure I can manage to do it this second way, but any suggestions are greatly appreciated none-the-less (not looking for working code).
Since nobody ever put it as a real answer, the MERGE command as mentioned by Mikael Eriksson in the comment is the right way to go, it worked great.
Here's a simple example usage:
MERGE dbo.DimProduct AS Target
USING (SELECT ProductID, ProductName, ProductColor, ProductCategory FROM dbo.StagingProduct) AS Source
ON (Target.ProductID = Source.ProductID)
WHEN MATCHED THEN
UPDATE SET Target.ProductName = Source.ProductName
WHEN NOT MATCHED BY TARGET THEN
INSERT (ProductID, ProductName, ProductColor, ProductCategory)
VALUES (Source.ProductID, Source.ProductName, Source.ProductColor, Source.ProductCategory)
OUTPUT $action, Inserted.*, Deleted.*;
from: http://www.bidn.com/blogs/bretupdegraff/bidn-blog/239/using-the-new-tsql-merge-statement-with-sql-server-2008
which helped me.
RedGate's SQL Compare product has automation capabilities.
http://downloads.red-gate.com/HelpPDF/ContinuousIntegrationForDatabasesUsingRedGateSQLTools.pdf
(I am not associated with redgate. I don't even like their products that much, but it seems to fit the case in this instance)