Let´s assume I have a Sentry with issues. Each issue has version field that holds version of app that user is using (e.g. 1.2.3, 0.5.0, ...).
Is it possible to create a bar graph widget that groups these releases in a graph by day (or other time interval)?
The result (in table notation, graph is preferred but if its not possible, table will work fine as well) for 2 found release tags for last 2 days would be like
-
1.0.0
2.0.0
3.10.2022
10
10
4.10.2022
5
50
I´ve tried to create a new widget with setting
• Visualization display -> Bar chart
• Query -> has:version (to filter only transactions that has version filled
• Y-Axis -> count_unique() with that version field
None of it worked as intended, does anyone have this use case solved?
Related
I just started with Superset a week ago and this is my first post.
Using Docker for latest code of the master Superset build.
I'm frustrated that as I configure queries that have multiple variables when I save the chart with no query errors shown and the queries listed in the Filters options -- the resultant chart is not dispaying the queries themselves.
I tried Cases first but the SQL editor kept generating errors, so I watched how Superset by default built Filters and then created queries with Custom SQL that satisfied Superset.
Here is a Partial chart query that includes filter queries producing table columns My intention is to create a stacked bar chart with no time increments , just total number of matching table records --
GROUP BY collection_id,
altersgruppe,
story_ID,
art_interview,
story_collector,
form_interview,
stichwort,
geschlecht,
story_ort
ORDER BY `COUNT(collection_id)` DESC
LIMIT 1000) AS virtual_table
WHERE ((altersgruppe LIKE %’Baby-Boomer%’
OR altersgruppe LIKE ‘%Gen X%’
AND altersgruppe LIKE ‘%Gen Y%’
OR altersgruppe LIKE ‘%Gen Z%’)
AND (art_interview LIKE '%digital%'
OR art_interview LIKE '%persönlich%')
AND (form_interview LIKE '%Einzelinterview%'
OR form_interview LIKE '%Gruppeninterview%')
AND (stichwort LIKE '%Bestes Erlebnis%'
OR stichwort LIKE '%Schlechtestes Erlebnis%'
OR stichwort LIKE '%Überraschung%')
AND (geschlecht LIKE '%männlich%' OR geschlecht LIKE '%weiblich%' OR geschlecht LIKE '%divers%'))
LIMIT 10;
Yesterday I saw a reference to adding these filter displays manually in the code.
But I decided I'd better check in here first.
I'm using one table in a mysql environment and can provide more data when asked.
It is my hope that some users recognize some of the most likely issues with missing filters and can give me directions to investigate.
Otherwise I can post my total chart query and other settings that might help me get a solution.
I’m trying to determine which of the following has the better performance for updating a document in Firestore/NoSQL in general.
Suppose that there is a sub-collection:
friends:
- doc_id_sjfn
• last_name=Wang
• last_talked=10sec ago
• actual_user_id=wang1997
- doc_id_wokm
• last=Liu
• last_talked=12min ago
• actual_user_id=liu98
and the client attaches a listener to the sub-collection and displays the sub-collection in real-time on a list view.
Suppose that we want to change Wang’s last_talked to 15 sec ago with app engine over google cloud.
When updating the list, is the performance better when
A: delete document doc_id_sjfn and insert document with doc_id_sjfn_v2 as ID
B: update field ‘last_talked’ of document doc_id_sjfn to 15 seconds ago
Since there are warnings against updating a document in-place for more than once per second, would approach A have better performance in terms of how long it takes for the change to be reflected on the list displayed on the client device? Under what condition is this faster? (If fields are indexed vs not indexed) (if the list view contains every element under the collection vs a subset of all elements under the collection using “where”)
Thanks!
(The example was edited; there are definitely better ways of implementing this use case, but the example is here to help me express the idea of using document as a view and needing constant refresh)
The rule of once per second is for specific documents. From the looks of the data it doesn't look like data that will update more than once per... year?
I wouldn't worry about the once per second with the data set presented and just update in place. You'll introduce a headache trying to reconcile old and new documents, e.g. you have v1, how do you know there isn't a v2?
I've created a chart in Oracle APEX 5 with 3 different data series:
Series 1: Line
Series 2: Bar
Series 3: Line
I've enabled multiple y-axis with different scales.
When I create Series 1, it uses primary y-axis automatically (as expected).
When I add Series 2, it uses extra y-axis automatically (as expected).
When I add Series 3, all three series start using the primary y-axis (unexpected).
I want Series 1 and 3 to use the primary y-axis and Series 2 to use the extra y-axis. I had created similar chart before and it worked fine. This time I'm unable to get Series 2 to use the secondary y-axis, please help!
Thanks!
Based on Hilary's sample application, the 2nd series should be the one used for the extra y-axis.
https://apex.oracle.com/pls/apex/f?p=36648:7
You may get a response from the APEX dev team if you ask in the OTN forums, especially if you provide a sample on apex.oracle.com
I'm new in tableau, and I'm trying to build a report.
I have a field of versions,
e.g: 36.0.0.8667, 39.0.0.8267, 42.0.0.9639, 42.0.0.10249.
I need to find the two newest versions (meaning the highest value in the first part, from that group the highest value in the second part etc...) and make a comparison between the two of them and the average for all versions (between dates).
Does anyone have any idea how can I find the two newest versions?
Thanks!
tablelau for dashboard right?
you just need filter that can get 2 biggest valu from database
example like this.
the output will be 2 biggest value
select max(p.total),a.tot from product p,(select max(`total`) as tot from `product`) as a where total < (select max(`total`) from `product`);
Can anyone of you please elaborate on how to map the informatica for the inserts and updates to the target from source table?
I appreciate it, if you explain with example.
TYPE2 Only INSERTS(New Rows as well as Updated Rows)
Version Data Mapping:
The Type 2 Dimension/Version Data mapping filters source rows based on user-defined comparisons and inserts both new and changed dimensions into the target. Changes are tracked in the target table by versioning the primary key and creating a version number for each dimension in the table. In the Type 2 Dimension/Version Data target, the current version of a dimension has the highest version number and the highest incremented primary key of the dimension.
Use the Type 2 Dimension/Version Data mapping to update a slowly changing dimension table when you want to keep a full history of dimension data in the table. Version numbers and versioned primary keys track the order of changes to each dimension.
When you use this option, the Designer creates two additional fields in the target:
PM_PRIMARYKEY. The Integration Service generates a primary key for each row written to the target.
PM_VERSION_NUMBER. The Integration Service generates a version number for each row written to the target.
Creating a Type 2 Dimension/Effective Date Range Mapping
The Type 2 Dimension/Effective Date Range mapping filters source rows based on user-defined comparisons and inserts both new and changed dimensions into the target. Changes are tracked in the target table by maintaining an effective date range for each version of each dimension in the target. In the Type 2 Dimension/Effective Date Range target, the current version of a dimension has a begin date with no corresponding end date.
Use the Type 2 Dimension/Effective Date Range mapping to update a slowly changing dimension table when you want to keep a full history of dimension data in the table. An effective date range tracks the chronological history of changes for each dimension.
When you use this option, the Designer creates the following additional fields in the target:
PM_BEGIN_DATE. For each new and changed dimension written to the target, the Integration Service uses the system date to indicate the start of the effective date range for the dimension.
PM_END_DATE. For each dimension being updated, the Integration Service uses the system date to indicate the end of the effective date range for the dimension.
PM_PRIMARYKEY. The Integration Service generates a primary key for each row written to the target.
The Type 2 Dimension/Flag Current mapping
The Type 2 Dimension/Flag Current mapping filters source rows based on user-defined comparisons and inserts both new and changed dimensions into the target. Changes are tracked in the target table by flagging the current version of each dimension and versioning the primary key. In the Type 2 Dimension/Flag Current target, the current version of a dimension has a current flag set to 1 and the highest incremented primary key.
Use the Type 2 Dimension/Flag Current mapping to update a slowly changing dimension table when you want to keep a full history of dimension data in the table, with the most current data flagged. Versioned primary keys track the order of changes to each dimension.
When you use this option, the Designer creates two additional fields in the target:
PM_CURRENT_FLAG. The Integration Service flags the current row “1” and all previous versions “0.”
PM_PRIMARYKEY. The Integration Service generates a primary key for each row written to the target.
You can start by looking at the Definition of SCD type-2 here.
http://en.wikipedia.org/wiki/Slowly_changing_dimension#Type_2
This implementation is so common in data warehouses that Informatica actually provides you with the template to do so. You can just "plug-in" your table names and the attributes.
If you have informatica installed, you can go to the following location in the help guide to see the detailed implementation logic.
Contents > Designer Guide > Using the mapping wizards > Creating a type 2 dimension.
Use a router to define groups for UPDATE and INSERT. Pass the output of each group to update strategy and then to target. HTH.