I am very new to Qubole.We recently migrated Oracle ebiz data to Saleforce.We have both Ebiz and Salesforce data in the Qubole Data Lake.There are some discrepancies between Ebiz and Salesforce.What is the technology I can use on Qubole to find these discrepancies?
This is approach I am using to compare two tables.
Aggregate all metrics in two tables group by all dimensions, then compare using FULL JOIN, it will return all joined and not joined records from both tables. In such way you can found absent data in both tables and differences in metrics.
For example like this, using Hive:
with
sf as (
select dimension1, dimension2, ... dimensionN,
sum(metric1) as metric1,
sum(metric2) as metric2,
...
sum(metricN) as metricN,
count(*) as cnt
from Salesforce_table
group by dimension1, dimension2, ... dimensionN
),
eb as (
select dimension1, dimension2, ... dimensionN,
sum(metric1) as metric1,
sum(metric2) as metric2,
...
sum(metricN) as metricN,
count(*) as cnt
from Ebiz_table
group by dimension1, dimension2, ... dimensionN
)
--compare data
select sf.*, eb.*
from sf full join eb on NVL(sf.dimension1,'')=NVL(eb.dimension1)
and sf.dimension2=eb.dimension2
...
and sf.dimension3=eb.dimension3
--Filter discrepancies only
where ( sf.metric1!=eb.metric1
or sf.metric2!=eb.metric2
...
or sf.metricN!=eb.metricN
or sf.cnt!=eb.cnt
or sf.dimension1 is null
or eb.dimension1 is null
)
Also you can easily compare in Excel instead of filtering in the WHERE.
Metrics are everything that can be aggregated. You can use some dimensions as metrics also like this count(distinct user) as user_cnt and group by date, site_name for example. Query with full join will show differences. If some dimensions used in join condition can be null, use nvl() to match such rows like in my example. Of course do not use too many dimensions in the groupby, you can skip some of them and drill down only after finding discrepancies on aggregated level.
After you got discrepancy in aggregations, you can drill down and compare rows not aggregated, filtered by some metrics.
See also: https://stackoverflow.com/a/67382947/2700344
Related
So I'd like make a query that shows all the datasets from a project, and the number of tables in each one. My problem is with the number of tables.
Here is what I'm stuck with :
SELECT
smt.catalog_name as `Project`,
smt.schema_name as `DataSet`,
( SELECT
COUNT(*)
FROM ***DataSet***.INFORMATION_SCHEMA.TABLES
) as `nbTable`,
smt.creation_time,
smt.location
FROM
INFORMATION_SCHEMA.SCHEMATA smt
ORDER BY DataSet
The view INFORMATION_SCHEMA.SCHEMATA lists all the datasets from the project the query is executed, and the view INFORMATION_SCHEMA.TABLES lists all the tables from a given dataset.
The thing is that the view INFORMATION_SCHEMA.TABLES needs to have the dataset specified like this give the tables informations : dataset.INFORMATION_SCHEMA.TABLES
So what I need is to replace the *** DataSet*** by the one I got from the query itself (smt.schema_name).
I am not sure if I can do it with a sub query, but I don't really know how to manage to do it.
I hope I'm clear enough, thanks in advance if you can help.
You can do this using some procedural language as follows:
CREATE TEMP TABLE table_counts (dataset_id STRING, table_count INT64);
FOR record IN
(
SELECT
catalog_name as project_id,
schema_name as dataset_id
FROM `elzagales.INFORMATION_SCHEMA.SCHEMATA`
)
DO
EXECUTE IMMEDIATE
CONCAT("INSERT table_counts (dataset_id, table_count) SELECT table_schema as dataset_id, count(table_name) from ", record.dataset_id,".INFORMATION_SCHEMA.TABLES GROUP BY dataset_id");
END FOR;
SELECT * FROM table_counts;
This will return something like:
I have three different tables. I want to select different columns from each of the tables and create one table based on some filters. Have a look at the following dax expression:
FILTER(DISTINCT(SELECTCOLUMNS(Test_Table,"site_key",[site_key],"is_active",[is_active])),[is_active]=TRUE&&[dbsource]=="DB2")
As you can see, I've selected olumns from Test_Table.
Firstly, How can I add columns from the other two tables?
Secondly, please note that these tables are related so I've created a relationship between them based on relevant IDs.
Will I have to create a natural join in DAX as well?
As I mentioned in the comment, SUMMARIZECOLUMNS can probably get you what you're looking for. It might look something like this in your case:
SUMMARIZECOLUMNS (
Test_Table[site_key],
Test_Table_2[industry_group],
Test_Table_2[country],
Test_Table_2[state],
FILTER ( Test_Table, [is_active] = TRUE && [dbsource] = "DB2" )
)
From
https://cloud.google.com/bigquery/docs/partitioned-tables:
you can shard tables using a time-based naming approach such as [PREFIX]_YYYYMMDD
This enables me to do:
SELECT count(*) FROM `xxx.xxx.xxx_*`
and query across all the shards. Is there a special notation that queries only the latest shard? For example say I had:
xxx_20180726
xxx_20180801
could I do something along the lines of
SELECT count(*) FROM `xxx.xxx.xxx_{{ latest }}`
to query xxx_20180801?
SINGLE QUERY INSPIRED BY Mikhail Berlyant:
SELECT count(*) as c FROM `XXX.PREFIX_*` WHERE _TABLE_SUFFIX IN ( SELECT
SUBSTR(MAX(table_id), LENGTH('PREFIX_') + 2)
FROM
`XXX.__TABLES_SUMMARY__`
WHERE
table_id LIKE 'PREFIX_%')
If you do care about cost (meaning how many tables will be scaned by your query) - the only way to do so is to do in two steps like below
First query
#standardSQL
SELECT SUBSTR(MAX(table_id), LENGTH('PREFIX') + 1)
FROM `xxx.xxx.__TABLES_SUMMARY__`
WHERE table_id LIKE 'PREFIX%'
Second Query
#standardSQL
SELECT COUNT(*)
FROM `xxx.xxx.PREFIX_*`
WHERE _TABLE_SUFFIX = '<result of first query>'
so, if result of first query is 20180801 so, second query will obviously look like below
#standardSQL
SELECT COUNT(*)
FROM `xxx.xxx.PREFIX_*`
WHERE _TABLE_SUFFIX = '20180801'
If you don't care about cost but rather need just result - you can easily combine above two queries into one - but - again - remember - even though result will be out of last table - cost will be as you query all table that match xxx.xxx.PREFIX_*
Forgot to mention (even though it should be obvious): of course when you have only COUNT(1) in your SELECT - the cost will be 0(zero) for both options - but in reality - most likely you will have something more valuable than just count(1)
I know this is a kind of an old thread but I was surprised why no one offers an answer using Variables.
"Héctor Neri" already mentioned this in the comments but I thought might be better to have an actual answer with a sample code posted.
#standardSQL
DECLARE SHARD_DATE STRING;
SET SHARD_DATE=(
SELECT MAX(REPLACE(table_name,'{TABLE}_',''))
FROM `{PRJ}.{DATASET}.INFORMATION_SCHEMA.TABLES`
WHERE table_name LIKE '{TABLE}_20%'
);
SELECT * FROM `{PRJ}.{DATASET}.{TABLE}_*`
WHERE _TABLE_SUFFIX = SHARD_DATE
Make sure to replace {PRJ}, {DATASET}, and {TABLE} values with your table location.
If you run this on BigQuery Web UI, you will see this message:
WARNING: Could not compute bytes processed estimate for script.
But you can see that variable properly reduce the table scan to the latest partition and does not cause any extra cost after running the script.
I want to check the partition lists in Athena.
I used query like this.
show partitions table_name
But I want to search specific table existed.
So I used query like below but there was no results returned.
show partitions table_name partition(dt='2010-03-03')
Because dt contains hour data also.
dt='2010-03-03-01', dt='2010-03-03-02', ...........
So is there any way to search when I input '2010-03-03' then it search '2010-03-03-01', '2010-03-03-02'?
Do I have to separate partition like this?
dt='2010-03-03', dh='01'
And show partitions table_name returned only 500 rows in Hive. Is the same in Athena also?
In Athena v2:
Use this SQL:
SELECT dt
FROM db_name."table_name$partitions"
WHERE dt LIKE '2010-03-03-%'
(see the official aws docs)
In Athena v1:
There is a way to return the partition list as a resultset, so this can be filtered using LIKE. But you need to use the internal information_schema database like this:
SELECT partition_value
FROM information_schema.__internal_partitions__
WHERE table_schema = '<DB_NAME>'
AND table_name = '<TABLE_NAME>'
AND partition_value LIKE '2010-03-03-%'
class Log:
project = ForeignKey(Project)
msg = CharField(...)
date = DateField(...)
I want to select the four most recent Log entries where each Log entry must have a unique project foreign key. I've tries the solutions on google search but none of them works and the django documentation isn't that very good for lookup..
I tried stuff like:
Log.objects.all().distinct('project')[:4]
Log.objects.values('project').distinct()[:4]
Log.objects.values_list('project').distinct('project')[:4]
But this either return nothing or Log entries of the same project..
Any help would be appreciated!
Queries don't work like that - either in Django's ORM or in the underlying SQL. If you want to get unique IDs, you can only query for the ID. So you'll need to do two queries to get the actual Log entries. Something like:
id_list = Log.objects.order_by('-date').values_list('project_id').distinct()[:4]
entries = Log.objects.filter(id__in=id_list)
Actually, you can get the project_ids in SQL. Assuming that you want the unique project ids for the four projects with the latest log entries, the SQL would look like this:
SELECT project_id, max(log.date) as max_date
FROM logs
GROUP BY project_id
ORDER BY max_date DESC LIMIT 4;
Now, you actually want all of the log information. In PostgreSQL 8.4 and later you can use windowing functions, but that doesn't work on other versions/databases, so I'll do it the more complex way:
SELECT logs.*
FROM logs JOIN (
SELECT project_id, max(log.date) as max_date
FROM logs
GROUP BY project_id
ORDER BY max_date DESC LIMIT 4 ) as latest
ON logs.project_id = latest.project_id
AND logs.date = latest.max_date;
Now, if you have access to windowing functions, it's a bit neater (I think anyway), and certainly faster to execute:
SELECT * FROM (
SELECT logs.field1, logs.field2, logs.field3, logs.date
rank() over ( partition by project_id
order by "date" DESC ) as dateorder
FROM logs ) as logsort
WHERE dateorder = 1
ORDER BY logs.date DESC LIMIT 1;
OK, maybe it's not easier to understand, but take my word for it, it runs worlds faster on a large database.
I'm not entirely sure how that translates to object syntax, though, or even if it does. Also, if you wanted to get other project data, you'd need to join against the projects table.
I know this is an old post, but in Django 2.0, I think you could just use:
Log.objects.values('project').distinct().order_by('project')[:4]
You need two querysets. The good thing is it still results in a single trip to the database (though there is a subquery involved).
latest_ids_per_project = Log.objects.values_list(
'project').annotate(latest=Max('date')).order_by(
'-latest').values_list('project')
log_objects = Log.objects.filter(
id__in=latest_ids_per_project[:4]).order_by('-date')
This looks a bit convoluted, but it actually results in a surprisingly compact query:
SELECT "log"."id",
"log"."project_id",
"log"."msg"
"log"."date"
FROM "log"
WHERE "log"."id" IN
(SELECT U0."id"
FROM "log" U0
GROUP BY U0."project_id"
ORDER BY MAX(U0."date") DESC
LIMIT 4)
ORDER BY "log"."date" DESC