I have a view in BQ. What I need is to handle manual overrides which sometimes might be applied to the view. Is there a way to keep the data from BQ saved in Google Sheets as well to be able to edit data there? It would be like: Big Query => Google Sheets => Big Query data flow.
Is there any other smart and efficient way to handle the problem?
If I understand correctly, you have some (small) tables that you want to occasionally edit by hand to fix up your existing data.
So:
Large table stored in BigQuery.
View over large table.
Small table of overrides for the view (kept in Sheets).
Query output (kept in Sheets).
As Tim mentions, if you create a federated table, you can use that as both input or output for a query.
So that all sounds pretty reasonable. Another option you might consider is embedding the overrides directly into the view (either as a JOIN against literal values or a CASE statement). That may execute more quickly, but might be less convenient to edit if you need to do that frequently.
Related
I have a list of IPs that I want to filter out of many queries that I have in sumo logic. Is there a way to store that list of IPs somewhere so it can be referenced, instead of copy pasting it in every query?
For example, in a perfect world it would be nice to define a list of things like:
things=foo,bar,baz
And then in another query reference it:
where mything IN things
Right now I'm just copying/pasting. I think there may be a way to do this by setting up a custom data source and putting the IPs in there, but that seems like a very round-about way of doing it, and wouldn't help to re-use parts of a query that aren't data (eg re-use statements). Also their template feature is about parameterizing a query, not re-use across many queries.
Yes. There's a notion of Lookup Tables in Sumo Logic. Consult:
https://help.sumologic.com/docs/search/lookup-tables/create-lookup-table/
for details.
It allows to store some values (either manually once, or in a scheduled way as as a result of some query) with | save operator.
And then you can refer to these values using | lookup which is conceptually similar to SQL's JOIN.
Disclaimer: I am currently employed by Sumo Logic.
I'm wondering about something that doesn't seem efficient to me.
I have 2 tables, one very large table DATA (millions of rows and hundreds of cols), with an id as primary key.
I then have another table, NEW_COL, with variable rows (1 to millions) but alwas 2 cols : id, and new_col_name.
I want to update the first table, adding the new_data to it.
Of course, i know how to do it with a proc sql/left join, or a data step/merge.
Yet, it seems inefficient, as far as I see with time executing, (which may be wrong), these 2 ways of doing rewrite the huge table completly, even when NEW_DATA is only 1 row (almost 1 min).
I tried doing 2 sql, with alter table add column then update, but it's waaaaaaaay too slow as update with joining doesn't seem efficient at all.
So, is there an efficient way to "add a column" to an existing table WITHOUT rewriting this huge table ?
Thanks!
SAS datasets are row stores and not columnar stores like tables in other databases. As such, adding rows is far easier and efficient than adding columns. A key joined view could be argued as the most 'efficient' way to add a column to a data rectangle.
If you are adding columns so often that the 1 min resource incursion is a problem you may need to upgrade hardware with faster drives, less contentious operating environment, or more memory and SASFILE if the new columns are often yet temporary in nature.
#Richard answer is perfect. If you are adding columns on regular basis then there is problem with your design. You either need to give more details on what you are doing and someone can suggest you.
I would try hash join. you can find code for simple hash join. This is efficient way of joining because in your case you have one large table and one small table if it fit into memory, it much better than a left join. I have done various joins using and query run times was considerably less( to order of 10)
By Altering table approach you are rewriting the table and also it causes lock on your table and nobody can use the table.
You should perform this joins when workload is less, which means during not during office and you may need to schedule the jobs in night, when more SAS resources are available
Thanks for your answers guys.
To add information, i don't have any constraint about table locking, balance load or anything as it's a "projet tool" script I use.
The goal is, in data prep step 'starting point data generator', to recompute an already existing data, or add a new one (less often but still quite regularly). Thus, i just don't want to "lose" time to wait for the whole table to rewrite while i only need to update one data for specific rows.
When i monitor the servor, the computation of the data and the joining step are very fast. But when I want tu update only 1 row, i see the whole table rewriting. Seems a waste of ressource to me.
But it seems it's a mandatory step, so can't do much about it.
Too bad.
There is a Java Swing application which uses an Informix database. I have user rights granted for the Swing application (i.e. no source code), and read only access to a mirror of the database.
Sometimes I need to find a database column, which is backing a GUI element (TextBox, TableField, Label...). What would be best approach to find out which database column and table is holding the data shown e.g. in a TextBox?
My general approach is to capture the state of the database. Commit a change using the GUI and then capture the state of the database again. Then I need to examine the difference. I've already tried:
Use the nrows field of systables: Didn't work, because the number in nrows does not seem to be a realtime representation of the row count.
Create a script with SELECT COUNT(*) ... for all tables: didn't work because too many tables (> 5000). Also tried to optimize by removing empty tables, but there are still too many left.
Is there a simple solution that I'm missing?
Please look at the Change Data Capture API and check if this suits your needs
There probably isn't a simple solution.
You probably need to build yourself a map of the database, or a data dictionary for it. It sounds as though you can eliminate many of the tables from consideration since they're empty — at least for a preliminary pass. If you're dealing with information in a text box, the chances are it is some sort of character data; you can analyze which (non-empty) tables which contain longer character strings, and they'd be the primary targets of your searches. If the schema is badly designed with lots of VARCHAR(255) columns even though the columns normally only hold short strings, life is more difficult. Over time, you can begin to classify tables and columns so that you end up knowing where to look for parts of the application.
One problem to beware of: the tabid in informix.systables isn't necessarily as stable as you'd like. Your data dictionary needs to record its own dd_tabid for the table it describes, and can store the last known tabid from informix.systables, but it needs to be ready to find a new tabid value on occasion. You should probably only mark data in your dictionary for logical deletion.
To some extent, this assumes you can create a database in which to record this information. If you can't create an Informix database, you may have to use something else (MySQL, or SQLite, perhaps) to store the data dictionary. Alternatively, go to your DBA team and ask them for the information. Unless you're trying something self-evidently untoward, they're likely to help (but politics can get in the way — I've no idea how collegial your teams are).
I am returning an entire table as a JSON call, no problem. without things like Stored Procs, I see the row/car layouts as the only filtering mechanism... is it possible to query the filtered row layout (ex: 1HqI7qIUMB-_52YHwWULUkF5LrnM5Ocp5OlYOiwQ#rows:id=5)? I can, of course, apply the same filters in the SQL WHERE claus... but why if i dont have to? When i apply the "#rows:id=5" on my current query, nothing is returned.
Currently there's no way to get at the filters in a particular row layout via the API; you'll just have to replicate the SQL as you say. It's an interesting idea, though, so I'd recommend filing a feature request with the issue tracker.
Rod
This is probably a very simple question that I am working through in an MVC project. Here's an example of what I am talking about.
I have an rdml file linked to a database with a table called Users that has 500,000 rows. But I only want to find the Users who were entered on 5/7/2010. So let's say I do this in my UserRepository:
from u in db.GetUsers() where u.CreatedDate = "5/7/2010" select u
(doing this from memory so don't kill me if my syntax is a little off, it's the concept I am looking for)
Does this statement first return all 500,000 rows and then filter it or does it only bring back the filtered list?
It filters in the database since your building your expression atop of an ITable returning a IQueryable<T> data source.
Linq to SQL translates your query into SQL before sending it to the database, so only the filtered list is returned.
When the query is executed it will create SQL to return the filtered set only.
One thing to be aware of is that if you do nothing with the results of that query nothing will be queried at all.
The query will be deferred until you enumerate the result set.
These folks are right and one recommendation I would have is to monitor the queries that LinqToSql is creating. LinqToSql is a great tool but it's not perfect. I've noticed a number of little inefficiencies by monitoring the queries that it creates and tweaking it a bit where needed.
The DataContext has a "Log" property that you can work with to view the queries created. I created a simple HttpModule that outputs the DataContext's Log (formatted for sweetness) to my output window. That way I can see the SQL it used and adjust if need be. It's been worth its weight in gold.
Side note - I don't mean to be negative about the SQL that LinqToSql creates as it's very good and efficient almost every time. Another good side effect of monitoring the queries is you can show your friends that are die-hard ADO.NET - Stored Proc people how efficient LinqToSql really is.