I'm new to InfluxDB. I currently have two databases in influx. I now want to copy certain data points from a measurement in the database1, then I want to introduce a couple field sets manually and modify the few field values that I copied and finally insert the changed data points in database2 under a different measurement.
I can use the select into statement however that will not allow me to make changes to the datapoint.
If I use the Insert command I will have to type all the field sets and tag sets individually.
I have a solution that I can use python and query the data points and manipulate the data then insert it back. However that will be a lengthy process.
Is there any easy way to accomplish this task?
Thanks.
Related
Informatica automatically inserts all the rows to the target...so why do we have to use update strategy transformation (DD_INSERT) to insert the records???
Good Question and you don't have to in case of insert only/update only case.
This assumption that informatica automatically inserts all the rows to the target is not true always. Yes, by default it inserts but there are many cases when we want to only update/only insert/delete/insert or update/reject the data.
Update strategy is used to control those scenarios.
DD_INSERT - This option is only to insert data.
DD_UPDATE - This updates the data based on key defined in target.
DD_REJECT - This rejects the data.
DD_DELETE - This deletes the data based on key defined in target.
Session should be data driven.
So, in your case, you can either mention dd_insert or set the session properties to insert only.
if you want to insert new data but update old data, you need to use dd_insert or dd_update.
if you want to insert new data but ignore old data, you need to use dd_insert or dd_reject.
if you want to only update old data, you need to use dd_update or set the session properties to update only..
Update strategy transformation is used when you want handy logic to check insert/update/delete records by comparing source key columns with target key columns. for each type of update strategy transformation, you can choose how you want to process your data. below link examples by Informatica will help you to understand this:
https://docs.informatica.com/data-integration/powercenter/10-5/transformation-language-reference/constants/dd_insert/examples.html
You can achieve the same by using a lookup and setting IUD Flag in expression transformation and then based on each flag you can route different types of records (ins, upd, del) into different target to update target in different ways.
Informatica is giving you read to use logic in the form of Update strategy transformation and dd_insert is one type of that.
While it is true that insert is the default behavior, it may be changed on session properties. See the Treat Source Rows As property documentation.
Only when you want to build a logic and decide what to do with a particular row, you should use Data Driven property value and then use DD_INSERT and other values according to your needs.
We have a scenario where we want to frequently change the tag of a (single) measurement value.
Our goal is to create a database which is storing prognosis values. But it should never loose data and track changes to already written data, like changes or overwriting.
Our current plan is to have an additional field "write_ts", which indicates at which point in time the measurement value was inserted or changed, and a tag "version" which is updated with each change.
Furthermore the version '0' should always contain the latest value.
name: temperature
-----------------
time write_ts (val) current_mA (val) version (tag) machine (tag)
2015-10-21T19:28:08Z 1445506564 25 0 injection_molding_1
So let's assume I have an updated prognosis value for this example value.
So, I do:
SELECT curr_measurement
INSERT curr_measurement with new tag (version = 1)
DROP curr_mesurement
//then
INSERT new_measurement with version = 0
Now my question:
If I loose the connection in between for whatever reason in between the SELECT, INSERT, DROP:
I would get double records.
(Or if I do SELECT, DROP, INSERT: I loose data)
Is there any method to prevent that?
Transactions don't exist in InfluxDB
InfluxDB is a time-series database, not a relational database. Its main use case is not one where users are editing old data.
In a relational database that supports transactions, you are protecting yourself against UPDATE and similar operations. Data comes in, existing data gets changed, you need to reliably read these updates.
The main use case in time-series databases is a lot of raw data coming in, followed by some filtering or transforming to other measurements or databases. Picture a one-way data stream. In this scenario, there isn't much need for transactions, because old data isn't getting updated much.
How you can use InfluxDB
In cases like yours, where there is additional data being calculated based on live data, it's common to place this new data in its own measurement rather than as a new field in a "live data" measurement.
As for version tracking and reliably getting updates:
1) Does the version number tell you anything the write_ts number doesn't? Consider not using it, if it's simply a proxy for write_ts. If version only ever increases, it might be duplicating the info given by write_ts, minus the usefulness of knowing when the change was made. If version is expected to decrease from time to time, then it makes sense to keep it.
2) Similarly, if you're keeping old records: does write_ts tell you anything that the time value doesn't?
3) Logging. Do you need to over-write (update) values? Or can you get what you need by adding new lines, increasing write_ts or version as appropriate. The latter is a more "InfluxDB-ish" approach.
4) Reading values. You can read all values as they change with updates. If a client app only needs to know the latest value of something that's being updated (and the time it was updated), querying becomes something like:
SELECT LAST(write_ts), current_mA, machine FROM temperature
You could also try grouping the machine values together:
SELECT LAST(*) FROM temperature GROUP BY machine
So what happens instead of transactions?
In InfluxDB, inserting a point with the same tag keys and timestamp over-writes any existing data with the same field keys, and adds new field keys. So when duplicate entries are written, the last write "wins".
So instead of the traditional SELECT, UPDATE approach, it's more like SELECT A, then calculate on A, and put the results in B, possibly with a new timestamp INSERT B.
Personally, I've found InfluxDB excellent for its ability to accept streams of data from all directions, and its simple protocol and schema-free storage means that new data sources are almost trivial to add. But if my use case has old data being regularly updated, I use a relational database.
Hope that clear up the differences.
I created multiple fields to test output in grafana, however I want to delete the unwanted fields from influxdb, is there a way?
Q: I want to delete the unwanted fields from influxdb, is there a way?
A: Short answer. No. Up until the latest release 1.4.0, there is no straightforward way to do this.
The reason why this is so was because Influxdb is explicitly designed to optimise point creation. Thus functionalities for the "UPDATE" and "DELETE" side of things are compromised for it.
To drop fields of a given measurement, the easiest way would be to;
Retrieve the data out first
Modify its content
Drop the measurement
Re-insert the modified data back
Reference:
https://docs.influxdata.com/influxdb/v1.4/concepts/insights_tradeoffs/
I'm using EF 4.1 (Code First). I need to add/update products in a database based on data from an Excel file. Discussing here, one way to achieve this is to use dbContext.Products.ToList() to force loading all products from the database then use db.Products.Local.FirstOrDefault(...) to check if product from Excel exists in database and proceed accordingly with an insert or add. This is only one round-trip.
Now, my problem is there are two many products in the database so it's not possible to load all products in memory. What's the way to achieve this without multiplying round-trips to the database. My understanding is that if I just do a search with db.Products.FirstOrDefault(...) for each excel product to process, this will perform a round-trip each time even if I issue the statement for the exact same product several times ! What's the purpose of the EF caching objects and returning the cached value if it goes to the database anyway !
There is actually no way to make this better. EF is not a good solution for this kind of tasks. You must know if product already exists in database to use correct operation so you always need to do additional query - you can group multiple products to single query using .Contains (like SQL IN) but that will solve only check problem. The worse problem is that each INSERT or UPDATE is executed in separate roundtrip as well and there is no way to solve this because EF doesn't support command batching.
Create stored procedure and pass information about product to that stored procedure. The stored procedure will perform insert or update based on the existence of the record in the database.
You can even use some more advanced features like table valued parameters to pass multiple records from excel into procedure with single call or import Excel to temporary table (for example with SSIS) and process them all directly on SQL server. As last you can use bulk insert to get all records to special import table and again process them with single stored procedures call.
I'm creating a page where I want to make a history page. So I was wondering if there is any way to fetch all rows from multiple tables and then sort by their time? Every table has a field called "created_at".
So is there any way to fetch from all tables and sort without having Rails sorting them form me?
You may get a better answer, but I would presume you would need to
Create a History table with a Created date column, an autogenerated Id column, and any other contents you would like to expose [eg Name, Description]
Modify all tables that generate a "history" item to consume this new table via Foreign Key relationship on History.Id
"Mashing up" tables [ie merging different result sets into a single result set] is a very difficult problem, but you would effectively be doing the above anyway - just in the application layer, so why not do it correctly and more efficiently in the data layer.
Hope this helps :)
You would need to perform the sql like:
Select * from table order by created_at incr
: Store this into an array. Do this for each of the data sources, and then perform a merge sort on all the arrays in Ruby. Of course this will work well for small data sets, but once you get a data set that is large (ie: greater than will fit into memory) then you will have to use a different collect/merge algorithm.
So I guess the answer is that you do need to perform some sort of Ruby, unless you resort to the Union method described in another answer.
Depending on whether these databases are all on the same machine or not:
On same machine: Use OrderBy and UNION statements in your sql to return your result set
On different machines: You'll want to test this for performance, but you could use Linked Servers and UNION, ORDER BY. Alternatively, you could have ruby get the results from each db, and then combine them and sort
EDIT: From your last comment about different tables and not DB's; use something like this:
SELECT Created FROM table1
UNION
SELECT Created FROM table2
ORDER BY created