In an existing codebase some tables are now horizontally sharded within the same database but in different namespaces.
E.g. let's say there previously was a large table users which is now sharded by the country field so there are now the following tables: us.users, ca.users, es.users etc.
Since every single query to the tables already contains the country filter I was thinking of the following minimalistic adjustment so that there's no need to subclass the original model for every country manually or dynamically:
class SessionWithShardedTableSupport(Session):
""" Use sharded tables on the fly """
def connection(self, mapper=None, clause=None, bind=None, close_with_result=None, **kw):
if mapper and mapper.local_table.name == 'users':
mapper.local_table.schema = '???' # `us` or `ca` or `es`
return super().connection(mapper, clause, bind, close_with_result, **kw)
The solution would work fine if there was a way to get the country filter from the query from within the session but there doesn't seem any (at least inspecting both mapper & clause parameters didn't reveal them).
1) Is there a way to get the where clause / the filters from within the session?
2) Is there maybe a better way to adjust the table name / table namespace on the fly with minimalistic changes to the existing code?
Related
I'm using Grafana v9.3.2.2 on Azure Grafana
I have a line chart with labels of an ID. I also have an SQL table in which the IDs are mapped to simple strings. I want to alias the IDs in the label to the strings from the SQL
I am trying to look for a transformation to do the conversion.
There is a transformation called “rename by regex”, but that will require me to hardcode for each case. Is there something similar with which I don't have to hardcode for each case.
There is something similar for variables - https://grafana.com/blog/2019/07/17/ask-us-anything-how-to-alias-dashboard-variables-in-grafana-in-sql/. But I don't see anything for transformations.
Use 2 queries in the panel - one for data with IDs and seconds one for mapping ID to string. Then add transformation Outer join and use that field ID to join queries results into one result.
You may need to use also Organize fields transformation to rename, hide unwanted fields, so only right fields will be used in the label at the end.
Im currently using jOOQ to build my SQL (with code generation via the mvn plugin).
Executing the created query is not done by jOOQ though (Using vert.X SqlClient for that).
Lets say I want to select all columns of two tables which share some identical column names. E.g. UserAccount(id,name,...) and Product(id,name,...). When executing the following code
val userTable = USER_ACCOUNT.`as`("u")
val productTable = PRODUCT.`as`("p")
create().select().from(userTable).join(productTable).on(userTable.ID.eq(productTable.AUTHOR_ID))
the build method query.getSQL(ParamType.NAMED) returns me a query like
SELECT "u"."id", "u"."name", ..., "p"."id", "p"."name", ... FROM ...
The problem here is, the resultset will contain the column id and name twice without the prefix "u." or "p.", so I can't map/parse it correctly.
Is there a way how I can say to jOOQ to alias these columns like the following without any further manual efforts ?
SELECT "u"."id" AS "u.id", "u"."name" AS "u.name", ..., "p"."id" AS "p.id", "p"."name" AS "p.name" ...
Im using the holy Postgres Database :)
EDIT: Current approach would be sth like
val productFields = productTable.fields().map { it.`as`(name("p.${it.name}")) }
val userFields = userTable.fields().map { it.`as`(name("p.${it.name}")) }
create().select(productFields,userFields,...)...
This feels really hacky though
How to correctly dereference tables from records
You should always use the column references that you passed to the query to dereference values from records in your result. If you didn't pass column references explicitly, then the ones from your generated table via Table.fields() are used.
In your code, that would correspond to:
userTable.NAME
productTable.NAME
So, in a resulting record, do this:
val rec = ...
rec[userTable.NAME]
rec[productTable.NAME]
Using Record.into(Table)
Since you seem to be projecting all the columns (do you really need all of them?) to the generated POJO classes, you can still do this intermediary step if you want:
val rec = ...
val userAccount: UserAccount = rec.into(userTable).into(UserAccount::class.java)
val product: Product = rec.into(productTable).into(Product::class.java)
Because the generated table has all the necessary meta data, it can decide which columns belong to it, and which ones don't. The POJO doesn't have this meta information, which is why it can't disambiguate the duplicate column names.
Using nested records
You can always use nested records directly in SQL as well in order to produce one of these 2 types:
Record2<Record[N], Record[N]> (e.g. using DSL.row(table.fields()))
Record2<UserAccountRecord, ProductRecord> (e.g using DSL.row(table.fields()).mapping(...), or starting from jOOQ 3.17 directly using a Table<R> as a SelectField<R>)
The second jOOQ 3.17 solution would look like this:
// Using an implicit join here, for convenience
create().select(productTable.userAccount(), productTable)
.from(productTable)
.fetch();
The above is using implicit joins, for additional convenience
Auto aliasing all columns
There are a ton of flavours that users could like to have when "auto-aliasing" columns in SQL. Any solution offered by jOOQ would be no better than the one you've already found, so if you still want to auto-alias all columns, then just do what you did.
But usually, the desire to auto-alias is a derived feature request from a misunderstanding of what's the best approch to do something in jOOQ (see above options), so ideally, you don't follow down the auto-aliasing road.
Let me give a summary of what I've been attempting to do and the efficiency issues I've been running into:
Essentially I want my users to be able to select parameters to filter data from my database, then I want to pass relevant data which passes those filters from the controller.
However, these filters query on data from multiple different tables (that is, about 5-6 different tables), some of which are quite large (as in 100k+ rows). These tables are all related to what I want to show, e.g. Here is a bond that meets so and so criteria, which is issued by so and so issuer, which must meet these criteria, and so on.
From an end result, I only really need about 100 rows after querying based on the parameters given by the user, but it feels like I need to look at everything in every table because I dont know how strict the filters will be beforehand. e.g. With a starting universe of 100k sets of data, passing filter f1,f2 of Table 1 might leave 90k, but after passing through filter f3 of table 2, f4,f5,f6 of table 3, and so ..., we might end up with 100 or less sets of data that pass these parameters because the last filters checked might be quite strict.
How can I go about querying through these multiple different tables efficiently?
Doing a join between them seems like it'd yield some time complexity of |T_1||T_2||T_3||T_4||T_5||T_6| where T_i is the "size" of table i.
On the other hand, just looking through the other tables based off the ids of the ones that pass the previous filter (as in, id 5,7,8 pass filters in T_1, which of those ids then pass filters in T_2, then which of those pass filters in T_3 and so on) looks like it might(?) have time complexity of |T_1| + |T_2| + ... + |T_6|.
I'm relatively new to Ruby on Rails, so im not entirely sure all of the tools at my disposal that could help with optimizing this, but at the same time I'm not entirely sure how to best approach this algorithmically.
I have a DMN decision created in Decision Manager 7.3. I have a few data types created, all of which are "structures" (i.e. complex types) with nested fields. I have created a decision table of which the condition column is bound to one of these structures (Customer) and the output column is bound to a Result structure.
However, I would expect the column headers to reflect the structure of the objects as per the example here (step 9 onwards): https://access.redhat.com/documentation/en-us/red_hat_decision_manager/7.3/html-single/designing_a_decision_service_using_dmn_models/index#dmn-data-types-defining-proc_dmn-models
In the documentation example, the Loan_Qualification type has nested fields and these are shown as sub-columns in the table header.
My data types are defined as follows:
I have a Customer input node and a decision node defined as follows:
Yet in my decision table, the columns map to the top level object only as follows:
So any ideas as to what I might be missing? Thanks in advance.
UPDATE
I have used the answer given below by #karreiro which works for the outcome / action column, but inserting an Input Clause left or right adds a new top level column, not a sub column, which then looks like the following:
Is this something you expect the decision table editor to be able to do as well?
Your expectations are correct.
The DMN editor aims to support the auto-creation of fields for Structure Data Types (for output clauses https://issues.jboss.org/browse/DROOLS-3685, and input clauses https://issues.jboss.org/browse/DROOLS-4491).
However, momentarily, users need to create these fields manually:
See how to create here :-)
I have a class that contains a LINKMAP field called links. This class is used recursively to create arbitrary hierarchical groupings (something like the time-series example, but not with the fixed year/month/day structure).
A query like this:
select expand(links['2017'].links['07'].links['15'].links['10'].links) from data where key='AAA'
Returns the actual records contained in the last layer of "links". This works exactly as expected.
But a query like this (note the 10,11 in the second to last layer of "links"):
select expand(links['2017'].links['07'].links['15'].links['10','11'].links) from data where key='AAA'
Returns two rows of the last layer of "links" instead:
{"1000":"#23:0","1001":"#24:0","1002":"#23:1"}
{"1003":"#24:1","1004":"#23:2"}
Using unionAll or intersect (with or without UNWIND) results in this single record:
[{"1000":"#23:0","1001":"#24:0","1002":"#23:1"},{"1003":"#24:1","1004":"#23:2"}]
But nothing I've tried (including various attempts at "compound" SELECTs) will get the expand to work as it does with the original example (i.e. return the actual records represented in the last LINKMAP).
Is there a SQL syntax that will achieve this?
Note: Even this (slightly modified) example from the ODB docs does not result in a list of linked records:
select expand(records) from
(select unionAll(years['2017'].links['07'].links['15'].links['10'].links, years['2017'].links['07'].links['15'].links['11'].links) as records from data where key='AAA')
Ref: https://orientdb.com/docs/2.2/Time-series-use-case.html
I'm not sure of what you want to achieve, but I think it's worth trying with values():
select expand(links['2017'].links['07'].links['15'].links['10','11'].links.values()) from data where key='AAA'