I've a table of IP addresses. The table has two columns names starting_ip and ending_ip. The table looks like the following:
Now, let's say I have a random IP address. From that random Ip address, I want to know the city_name. That means I need to know that the random IP address falls between which range, based on starting_ip and ending_ip. Then find 1 record and get the city_name.
I wrote a query something like this:
class IpToCity < ActiveRecord::Base
establish_connection :"ip_database_#{Rails.env}"
scope :search_within_ip_range, -> (ip_address) do
self.connection.select_all("
with candidate as (
select * from ip_cities
where ending_ip >= '#{ip_address}'::inet
order by ending_ip asc
limit 1
)
select * from candidate
where starting_ip <= '#{ip_address}'::inet;
")
end
end
It's a scope, where I pass the random IP and get a single record. The problem is, the query works fine, but it's very slow. Any suggestion, how to make it faster?
Thanks in advance!
Do all the rows match this format?
starting_ip ending_ip
x.y.z.0 x.y.z.255
If so, then you can add another column for "prefix": x.y.z.
Then match the first 3 octets of the target against the prefix column.
When updating the DB, break rows that span more than one prefix into multiple rows.
The max number of rows is 16.8M (2563), which is small and only slightly bigger than your current 5M.
Related
I have a Kafka topic "events" which records user image votes and has json in the following structure:
{"category":"image","action":"vote","label":"amsterdam","ip":"1.1.1.1","value":2}
I need to receive on another topic the sum of all votes for the label (e.g. amsterdam) but drop any votes that came from the same IP address using only the last vote. This topic should have json in this format:
{label:”amsterdam”,SCORE:8,TOTAL:3}
SCORE is a sum of all votes and TOTAL is the number of votes counted.
The solution I made creates a stream from the topic events:
CREATE STREAM st_events
(CATEGORY STRING, ACTION STRING, LABEL STRING, VALUE BIGINT, IP STRING)
WITH (KAFKA_TOPIC='events', VALUE_FORMAT='JSON');
Then, I create a table tb_votes which calculates the score and total for each label and IP address:
CREATE TABLE tb_votes WITH (KAFKA_TOPIC='tb_votes', PARTITIONS=1, REPLICAS=1) AS SELECT
st_events.LABEL "label", SUM(st_events.VALUE-1) "score", CAST(COUNT(*) AS BIGINT) "total"
FROM st_events
WHERE
st_events.category='image' AND st_events.action='vote'
GROUP BY st_events.label, st_events.ip
EMIT CHANGES;
The problem is that instead of dropping all the previous votes coming from the same ip address for the same image, Kafka uses all of them. This makes sense as it is a GROUP BY.
Any idea how to "drop" all previous votes and only use the latest values for an image/ IP?
You need a two stage aggregation.
The first stage should build a table with a primary key containing both the ip and label and another column holding the value.
Build a second table from this first table to get the count and sum per-label that you need.
If another vote comes in from the same ip for the same label then the first table will be updated with the new value and the second table will be correctly updated. It will first remove the old value from the count and sum and then apply the new value.
ksqlDB does not yet support multiple primary key columns (though its coming VERY soon!). So when you group by two columns it just does a funky string concatenation. But we can work with that for now.
CREATE TABLE BY_IP_AND_LABEL AS
SELECT
label + '-' + ip AS ipAndLabel,
value
FROM st_events
GROUP BY ip + '#' + label;
CREATE TABLE BY_LABEL AS
SELECT
SUBSTRING(labelAndIp, INSTR(labelAndIp, '#')) AS label,
SUM(VALUE-1) AS score,
COUNT(*) AS total
FROM BY_IP_AND_LABEL
GROUP BY SUBSTRING(ipAndLabel, INSTR(ipAndLabel, '#'));
The first table creates a composite key with and # as the separator. The second table uses INSTR and SUBSTRING to find the separator and extract the label.
Note: I've not tested this - I could have some 'off-by-one' errors in the logic.
This should do what you need.
I'm trying to come up with a PostgreSQL schema for host data that's currently in an LDAP store. Part of that data is the list of hostnames a machine can have, and that attribute is generally the key that most people use to find the host records.
One thing I'd like to get out of moving this data to an RDBMS is the ability to set a uniqueness constraint on the hostname column so that duplicate hostnames can't be assigned. This would be easy if hosts could only have one name, but since they can have more than one it's more complicated.
I realize that the fully-normalized way to do this would be to have a hostnames table with a foreign key pointing back to the hosts table, but I'd like to avoid having everybody need to do joins for even the simplest query:
select hostnames.name,hosts.*
from hostnames,hosts
where hostnames.name = 'foobar'
and hostnames.host_id = hosts.id;
I figured using PostgreSQL arrays could work for this, and they certainly make the simple queries simple:
select * from hosts where names #> '{foobar}';
When I set a uniqueness constraint on the hostnames attribute, though, it of course treats the entire list of names as the unique value instead of each name. Is there a way to make each name unique across every row instead?
If not, does anyone know of another data-modeling approach that would make more sense?
The righteous path
You might want to reconsider normalizing your schema. It is not necessary for everyone to "join for even the simplest query". Create a VIEW for that.
Table could look like this:
CREATE TABLE hostname (
hostname_id serial PRIMARY KEY
, host_id int REFERENCES host(host_id) ON UPDATE CASCADE ON DELETE CASCADE
, hostname text UNIQUE
);
The surrogate primary key hostname_id is optional. I prefer to have one. In your case hostname could be the primary key. But many operations are faster with a simple, small integer key. Create a foreign key constraint to link to the table host.
Create a view like this:
CREATE VIEW v_host AS
SELECT h.*
, array_agg(hn.hostname) AS hostnames
-- , string_agg(hn.hostname, ', ') AS hostnames -- text instead of array
FROM host h
JOIN hostname hn USING (host_id)
GROUP BY h.host_id; -- works in v9.1+
Starting with pg 9.1, the primary key in the GROUP BY covers all columns of that table in the SELECT list. The release notes for version 9.1:
Allow non-GROUP BY columns in the query target list when the primary
key is specified in the GROUP BY clause
Queries can use the view like a table. Searching for a hostname will be much faster this way:
SELECT *
FROM host h
JOIN hostname hn USING (host_id)
WHERE hn.hostname = 'foobar';
Provided you have an index on host(host_id), which should be the case as it should be the primary key. Plus, the UNIQUE constraint on hostname(hostname) implements the other needed index automatically.
In Postgres 9.2+ a multicolumn index would be even better if you can get an index-only scan out of it:
CREATE INDEX hn_multi_idx ON hostname (hostname, host_id);
Starting with Postgres 9.3, you could use a MATERIALIZED VIEW, circumstances permitting. Especially if you read much more often than you write to the table.
The dark side (what you actually asked)
If I can't convince you of the righteous path, here is some assistance for the dark side:
Here is a demo how to enforce uniqueness of hostnames. I use a table hostname to collect hostnames and a trigger on the table host to keep it up to date. Unique violations raise an exception and abort the operation.
CREATE TABLE host(hostnames text[]);
CREATE TABLE hostname(hostname text PRIMARY KEY); -- pk enforces uniqueness
Trigger function:
CREATE OR REPLACE FUNCTION trg_host_insupdelbef()
RETURNS trigger
LANGUAGE plpgsql AS
$func$
BEGIN
-- split UPDATE into DELETE & INSERT
IF TG_OP = 'UPDATE' THEN
IF OLD.hostnames IS DISTINCT FROM NEW.hostnames THEN -- keep going
ELSE
RETURN NEW; -- exit, nothing to do
END IF;
END IF;
IF TG_OP IN ('DELETE', 'UPDATE') THEN
DELETE FROM hostname h
USING unnest(OLD.hostnames) d(x)
WHERE h.hostname = d.x;
IF TG_OP = 'DELETE' THEN RETURN OLD; -- exit, we are done
END IF;
END IF;
-- control only reaches here for INSERT or UPDATE (with actual changes)
INSERT INTO hostname(hostname)
SELECT h
FROM unnest(NEW.hostnames) h;
RETURN NEW;
END
$func$;
Trigger:
CREATE TRIGGER host_insupdelbef
BEFORE INSERT OR DELETE OR UPDATE OF hostnames ON host
FOR EACH ROW EXECUTE FUNCTION trg_host_insupdelbef();
SQL Fiddle with test run.
Use a GIN index on the array column host.hostnames and array operators to work with it:
Why isn't my PostgreSQL array index getting used (Rails 4)?
Check if any of a given array of values are present in a Postgres array
In case anyone still needs what was in the original question:
CREATE TABLE testtable(
id serial PRIMARY KEY,
refs integer[],
EXCLUDE USING gist( refs WITH && )
);
INSERT INTO testtable( refs ) VALUES( ARRAY[100,200] );
INSERT INTO testtable( refs ) VALUES( ARRAY[200,300] );
and this would give you:
ERROR: conflicting key value violates exclusion constraint "testtable_refs_excl"
DETAIL: Key (refs)=({200,300}) conflicts with existing key (refs)=({100,200}).
Checked in Postgres 9.5 on Windows.
Note that this would create an index using the operator &&. So when you are working with testtable, it would be times faster to check ARRAY[x] && refs than x = ANY( refs ).
P.S. Generally I agree with the above answer. In 99% cases you'd prefer a normalized schema. Please try to avoid "hacky" stuff in production.
I'd like to have a basic table summing up the number of occurence of values inside arrays.
My app is a Daily Deal app built to learn more Ruby on Rails.
I have a model Deals, which has one attribute called Deal_goal. It's a multiple select which is serialized in an array.
Here is the deal_goal taken from schema.db:
t.string "deal_goal",:array => true
So a deal A can have deal= goal =[traffic, qualification] and another deal can have as deal_goal=[branding, traffic, acquisition]
What I'd like to build is a table in my dashboard which would take each type of goal (each value in the array) and count the number of deals whose deal_goal's array would contain this type of goal and count them.
My objective is to have this table:
How can I achieve this? I think I would need to group each deal_goal array for each type of value and then count the number of times where this goals appears in the arrays. I'm quite new to RoR and can't manage to do it.
Here is my code so far:
column do
panel "top of Goals" do
table_for Deal.limit(10) do
column ("Goal"), :deal_goal ????
# add 2 columns:
'nb of deals with this goal'
'Share of deals with this goal'
end
end
Any help would be much appreciated!
I can't think of any clean way to get the results you're after through ActiveRecord but it is pretty easy in SQL.
All you're really trying to do is open up the deal_goal arrays and build a histogram based on the opened arrays. You can express that directly in SQL this way:
with expanded_deals(id, goal) as (
select id, unnest(deal_goal)
from deals
)
select goal, count(*) n
from expanded_deals
group by goal
And if you want to include all four goals even if they don't appear in any of the deal_goals then just toss in a LEFT JOIN to say so:
with
all_goals(goal) as (
values ('traffic'),
('acquisition'),
('branding'),
('qualification')
),
expanded_deals(id, goal) as (
select id, unnest(deal_goal)
from deals
)
select all_goals.goal goal,
count(expanded_deals.id) n
from all_goals
left join expanded_deals using (goal)
group by all_goals.goal
SQL Demo: http://sqlfiddle.com/#!15/3f0af/20
Throw one of those into a select_rows call and you'll get your data:
Deal.connection.select_rows(%q{ SQL goes here }).each do |row|
goal = row.first
n = row.last.to_i
#....
end
There's probably a lot going on here that you're not familiar with so I'll explain a little.
First of all, I'm using WITH and Common Table Expressions (CTE) to simplify the SELECTs. WITH is a standard SQL feature that allows you to produce SQL macros or inlined temporary tables of a sort. For the most part, you can take the CTE and drop it right in the query where its name is:
with some_cte(colname1, colname2, ...) as ( some_pile_of_complexity )
select * from some_cte
is like this:
select * from ( some_pile_of_complexity ) as some_cte(colname1, colname2, ...)
CTEs are the SQL way of refactoring an overly complex query/method into smaller and easier to understand pieces.
unnest is an array function which unpacks an array into individual rows. So if you say unnest(ARRAY[1,2]), you get two rows back: 1 and 2.
VALUES in PostgreSQL is used to, more or less, generate inlined constant tables. You can use VALUES anywhere you could use a normal table, it isn't just some syntax that you throw in an INSERT to tell the database what values to insert. That means that you can say things like this:
select * from (values (1), (2)) as dt
and get the rows 1 and 2 out. Throwing that VALUES into a CTE makes things nice and readable and makes it look like any old table in the final query.
In my ETL process I am using Change Data Capture (CDC) to discover only rows that have been changed in the source tables since the last extraction. Then I do the transformation only for this rows. The problem is when I have for example 2 tables which I want to join into one dimension, and only one of them has changed. For example I have table Countries and Towns as following:
Countries:
ID Name
1 France
Towns:
ID Name Country_ID
1 Lyon 1
Now lets say a new row is added to Towns table:
ID Name Country_ID
1 Lyon 1
2 Paris 2
The Countries table has not been changed, so CDC for these tables shows me only the row from Towns table. The problem is when I do the join between Countries and Towns, there is no row in Countries change set, so the join will result in empty set.
Do you have an idea how to solve it? Of course there might be more difficult cases, involving 3 and more tables, and consequential joins.
This is a typical problem found when doing Realtime Change-Data-Capture, or even Incremental-only daily changes.
There's multiple ways to solve this.
One way would be to do your joins on the natural keys in the dimension or mapping table, to get the associated country (SELECT distinct country_name, [..other attributes..] from dim_table where country_id = X).
Another alternative would be to do the join as part of the change capture process - when a row is loaded to towns, a trigger goes off that loads the foreign key values into the associated staging tables (country, etc).
There is allot i could babble on for more information on but i will be specific to what is in your question. I would suggest the following to get the results...
1st Pass is where everything matches via the join...
Union All
2nd Pass Gets all towns where there isn't a country
(left outer join with a where condition that
requires the ID in the countries table to be null/missing).
You would default the Country ID value in that unmatched join to something designated as a "Unmatched Value" typically 0 or -1 is used or a series of standard -negative numbers that you could assign descriptions to later to identify why data is bad for your example -1 could be "Found Town Without Country".
I have a table that gets populated every day with records from reporting systems.
I have a list of the serial numbers those i am interested in returning in an asset list.
How do I get Grails to return the records that match the maximum "epoch" entry for each asset? In sql I would cross join the table back to itself after picking out the maximum such as:
select a.* from assetTable a inner join (select sn, max(epoch) epoch from assetTable group by sn) b on a.sn = b.sn and a.epoch = b.epoch
but I cannot figure out how to get this done efficiently with Grails...
From a domain class perspective it is pretty simple. Consider for the same of example that I have a single domain class "AssetTable" and it has Integer epoch, String sn, ...
Literally, all I want to do is get the latest entry (all fields) for a subset of serial numbers (sn) that I have in a List.