I`m trying training a model with a little dataset (1000 rows), but Modeler flow of IBM Watson Studio takes too long time in "Running flow Status: Training model process completed, took 4 minutes and 20 seconds" state.
After this, result in generic error "Error: Unable to complete last action"
MORE INFOS
Modeling
Dataset:
Type:
Partition
Neural Net Modeling
Anybody know what the problem?
Related
We're using AWS Lightsail PostgreSQL Database. We've been experiencing errors with our C# application timing out when using the connection to database. As I'm trying to debug the issue, I went to look at the Metric graphs in AWS. I noticed that many of the graphs have frequent gaps in the data, labeled No data available. See image below.
This graph (and most of the other metrics) shows frequent gaps in the data. I'm trying to understand if this is normal, or could be a symptom of the problem. If I go back to 2 weeks timescale, there does not appear to be any other strange behaviors in any of the metric data. For example, I do not see a point in time in the past where the CPU or memory usage went crazy. The issue started happening about a week ago, so I was hoping the metrics would have helped explained why the connections to the PostgreSQL database are failing from C#.
🔶 So I guess my question is, are those frequent gaps of No data available normal for a AWS Lightsail Postgres Database?
Other Data about the machine:
1 GB RAM, 1 vCPU, 40 GB SSD
PostgreSQL database (12.11)
In the last two weeks (the average metrics show):
CPU utilization has never gone over 20%
Database connections have never gone over 35 (usually less than 5) (actually, usually 0)
Disk queue depth never goes over 0.2
Free storage space hovers around 36.5 GB
Network receive throughput is mostly less than 1 kB/s (with one spike to 141kB/s)
Network transmit throughput is mostly less than 11kB/s with all spikes less than 11.5kB/s
I would love to view the AWS logs, but they are a month old, and when trying to view them they are filled with checkpoint starting/complete logs. They start at one month ago and each page update only takes me 2 hours forward in time (and taking ~6 seconds to fetch the logs). This would require me to do ~360 page updates, and when trying, my auth timed out. 😢
So we never figured out the reason why, but this seems like it was a problem with the AWS LightSail DB. We ended up using a snapshot to create a new clone of the DB, and wiring the C# servers to the new DB. The latency issues we were having disappeared and the metric graphs looked normal (without the strange gaps).
I wish we were able to figure out the root of the problem. ATM, we are just hoping the problem does not return.
When in doubt, clone everything! 🙃
I’m working on a new project that will involve storing events from various systems at random intervals. Events such as deployment completions, production bugs, continuous integration events etc. This is somewhat time series data, although the volume should be relatively low, a few thousand a day etc.
I had been thinking maybe InfluxDB was a good option here as the app will revolve mostly around plotting time lines and durations etc, although there will need to be a small amount of data stored with these datapoints. Information like error messages , descriptions , url and maybe twitter sized strings. I would say that there is a good chance most events will not actually have a numerical value but more just act as a point in time reference for an event.
As an example, I would expect a lot of events to look like (in Influx line protocol format)
events,stream=engineering,application=circleci,category=error message="Web deployment failure - Project X failed at step 5", url=“https://somelink.com”,value=0
My question here is, am I approaching this wrong? Is InfluxDB the wrong choice for this type of data? I have read a few horror stories about data corruption and i’m a bit nervous there but i’m not entirely sure of any better (but also affordable) options.
How would you go about storing this type of data in a way that can can accessed at a high frequency for a purpose such as a realtime dashboard?
Im resisting the urge to just rollout a Postgres database.
There's a time critical application that handles messages from a trading server where we get around 10K msgs per second... There are times when the application tends to be taking a lot of time in doing the inserts in the database... After several days of going back and forth with the dev team about which side is taking the time, our db team decided to build a simple C# app that resides on a server on the same rack and the same network as the database server. The database in question is sql server 2012 standard.
The times were taken from ado.net this way...
var currT1 = DateTime.Now;
sqlComm.ExecuteNonQuery();
var loadT = DateTime.Now;
The times from sql server were taken from the startTime and endTime columns from a server side trace... The two servers are time-synched but there's a differences of 10-15 ms...
Now what's making me want to bang my head on something is that while it's understandable the application takes longer than the db (cuz it has to do processing as well as other stuff)... But in some cases, the DB reports it took 4 ms, but the app says it took zero ms!!
I definitely think the bug is with the test app... But there's nothing separating the db call and the two timestamps... The log reads like this... App times (start, end, diff, method) followed by db calls (starttime, endtime, diff)
10:46:06.716
10:46:06.716
0:00:00.000
DataAdapter
10:46:06.697
10:46:06.700
0:00:00.003
is there something else I should provide?
Based on the observations from you the helpful lot, we used the stopwatch class... Then we got an even weirder issue... We used the stopwatch.elapsedticks property thinking that dividing it by 10 would give us microseconds... the duration column in the server side trace is in microseconds because it's saved to a file. Still, the time from the application is less than from the database... As it turned out, the property to use was elapsed.tick and not the elapsedtick property to get the microseconds. Dividing elapsed.tick with 10 gave us the microseconds...
So there it is... got both the application and the db to give us very close to accurate (can't be sure ever :) ) times...
The conclusion that I have drawn is to not only not believe the datetime.now .net property but also the startTime and endTime server trace columns... calculating duration from dedicated timers is what's required...
Thanks for the heads up guys...
Follow the steps to generate the error:
1. Configure the large amount of data (around 4 GB or more than 50 millions of records)
2. Give proper data-config.xml file for indexing the data from remote database server.
3. During indexing the data into solr from SQL SERVER 2010, at the half way unplug the
network cable and see the status in solr. e.g.
localhost:8083/solr/core1/dataimport?command=status
or
localhost:8083/solr/core1/dataimport
4. Pass few seconds then again plug back the cable.
5. You can clearly see that there is just only "Time Elapsed" parameter increase.
"Total Rows Fetched" & "Total Documents Processed" remains same for infinite time.
6. You can regenerate this for small data also.
7. Work around is you need to restart the solr. (But this is not good solution)
Note: This is very important issue because, so many organizations not using this valuable
products just because of the this database infinite connection issue. Solution can be:
Forcefully abort the data indexing or provide mechanism for forcefully
abort the indexing. Hope you guys knows that abort command is also not
working.
From Solr documentation (http://wiki.apache.org/solr/DataImportHandler)
Abort an ongoing operation by hitting the URL
http://:/solr/dataimport?command=abort .
I just checked the source code for DIH and abort command is implemented
I am using JDeveloper 11.1.2.3.0
I have implemented af:calenar functionality in my application. My calendar is based in a ViewObject that queries a database table with a big number of records (500-1000). Performing the selection through a select query to my database table is very fast, only some ms. The problem is that the time to load of my af:calendar is too long. It requires more than 5 seconds. If I just want to change the month, or the calendar view I have to wait approximately that amount of time. I searched a lot through the net but I found no explanation to this. Can anyone please explain why it takes so long? Has anyone ever faced this issue?
PS: I have tested even with JDeveloper 12 and the problem is identically the same
You should look into the viewobject tuning properties to see how many records you fetch in a single network access, and do the same check for the executable that populates your calendar.
Also try using the HTTP Analyzer to see what network traffic is going on and the ADF Logger to check what SQL is being sent to the DB.
https://blogs.oracle.com/shay/entry/monitoring_adf_pages_round_trips