We are using unicorn 3.2.0 for sitecore 8.1 update 3.
I noticed where ever i did a sync from unicorn.aspx some items repeatedly modified even though they are unmodified.
UPM sync complete: 1740 items evaluated, 67 items modified (0 added, 67 updated, 0 recycled) in 9816ms (~5.6ms/item).
These 67 items are not modified. This keeps happening only to these set of items.
when i checked the log files i found:
14480 18:13:13 INFO [Unicorn]: > Field Key - Reset to standard value
14480 18:13:13 INFO [Unicorn]: * [U] Key
14480 18:13:13 INFO [Unicorn]: * [U] Value
I don't understand why these fields are reset to standard value? These two fields key and value are shared fields.
Let me know if u need more info
This has been fixed in Unicorn 4.0.4. A 4.0.4-pre1 release is available on NuGet.
More information here: https://sitecore.stackexchange.com/questions/9671/unicorn-always-serializes-items-which-have-fallback-enabled
Related
Using Power Query to query Kusto and the query times out after 5 minutes even though I've set the timeout to 21 minutes, like this:
[Timeout = #duration(0,0,21,0), ClientRequestProperties = [#"query_language" = "csl"]])
The query in question typically takes about 7-10 minutes when run directly in Kusto.
A similar question asked here had an answer that suggested going to "Data source settings" and clicking on "Change Source..." but that button is grayed for me. Besides, the above, query-specific setting should override a global setting, right?
Assuming that you're using the AzureDataExplorer.Contents() or Kusto.Contents() methods, there was a regression in the Timeout implementations of the connector. This was fixed on Jun 7 2021, and should be included in version 3.0.52 of the connector (should already be publicly available - make sure you have the latest version of the PBI Desktop).
If you're still facing an issue, contact me directly at itsagui(at)microsoft.com
We have 37 Informatica Sessions in which most of the Sessions have around 25 tables on average. Few sessions have 1 table as source and target. Our Source is Oracle and target is Greenplum database. We are using Powerexchange 10.1 installed on Oracle to fetch our Changed records.
We have noticed that for the sessions having more tables it is taking more time to fetch the data and update in target. Does adding more tables make any delay in Processing? In that case How to tune to fetch the records as fast as possible?
We run 19 CDC mappings with between 17 and 90 tables in each, and have recently had a breakthrough in performance. The number of tables is not the most significant limiting factor for us, power center and power exchange is. Our source is DB2 on z/OS, but that is probably not important ...
This is what we did:
1) we increased the DTM buffer block-size to 256KB, and DTM buffer size to 1GB or more, a 'complex' mapping needs many buffer blocks.
2) we change the connection attributes to:
- Realtime flush latency=86000 (max setting)
- Commit-size in session were set extremely high (to allow the above setting to be the deciding factor)
- OUW count=-1 (Same reason as above)
- maximum rows per commit=0
- minimum rows per commit=0
3) we set the session property 'recovery strategy' to 'fail task and continue workflow' and implemented our own solution to create a 'restart token file' from scratch every time the workflow starts.
Only slightly off topic: The way we implemented this was with an extra table (we call it a SYNC table) containing one row only. That row is being updated every 10 minutes on the source by very a reliable scheduled process (a small CICS program). The content of this table is written to the target database once per workflow and an extra column is added in the mapping, that contains the content of $$PMWorkflowName. Apart from the workflowname column, the two DTL__Restart1 and *2 columns is written to the target as well.
During startup of the workflow we run a small reusable session before the actual CDC session which reads the record for the current workflow from the SYNC table on the target side and creates the RESTART file from scratch.
[please note that you will end up with dublicates from up to 10 minutes (from workflow start time) in the target. We accept that and are aggregating it away in all mappings reading from these]
Try to tinker with combinations of these and tell what you experience. We now have a maximum throughput in a 10 minute interval of 10-100 million rows per mapping. Our target is Netezza (aka PDA from IBM)
One more thing I can tell you:
Every time a commit is triggered (each 86 seconds with the above settings) power center will empty all its writer buffers against all of the tables in one big commit scope. If either of these is locked by another process, you may end up with a lot of cascaded locking on the writer side, which will make the CDC seem slow.
I have below requirement. I have env.properties file which consists of Name/Value pairs and i have one more properties file that is being checked out from SVN to server machine where ANT is installed.
The env.prop file values will not change and remain constant.Example below shows 3 values but in real time scenario it can contain almost 20 to 30 values.
env.properties
DataProvider/JMS_Host/destination.value=127.0.0.1
DataProvider/JMS_Port/destination.value=8987
DataProvider/JMS_User/destination.value=admin
svn.properties
DataProvider/JMS_Host/destination.value=7899000--877##
DataProvider/JMS_Port/destination.value=
DataProvider/JMS_User/destination.value=##$%###
This properties file which is pulled out from svn (svn.properties) will contain the same Name but the values can differ or can be even blank.So aim is to replace the values in svn.properties file with the values from env.properties and end result should be with values from env.prop file.Any help would be really help. There is a similar request as per below link but it servers for only few values but when we have more than 20 to 30 tokens to replace which would be ugly way of implementation.
enter link description here
I recently came across this issue on opencart version 2.1.0.1 where if you have quite a lot of product options set and update the product they end up removing some of the options. In my case out of 133 option values 50 was removed without any reason.
The issue is later identified to be caused by low max_input_vars value in php.ini My default setup had 1000 which I later changed to 2000 and now the issue no longer prevalent :)
I am using Weka GUI to run a NaiveBayes classifier on an online post. I am trying to track the instances (online posts) that are incorrectly predicted so that I can learn further how I can improve the features.
Currently, I have a work around to do that: I generate the data with unique ID included, and when I import to Weka I remove the uniqueID. I then attach the prediction appender, which saves prediction results to an .arff file. I read through the file to find instances with bad performance. For incorrectly classified instances, I use certain feature values that give unique enough value for each instance and find the instance with the same value from my original data, which contains the unique ID. As you can see, this is a truly time consuming process.
I would love to hear if there is a way to ignore a feature, which in my case is the unique ID of an instance, while keeping it as part of the data when running the classifier.
Thank you.
I'm not sure if weka GUI has a direct option for that. However you can achieve the same through commandline
java weka.classifiers.meta.FilteredClassifier -F weka.filters.unsupervised.attribute.RemoveType -W weka.classifiers.trees.RandomForest -t G:\pub-resampled-0.5.arff -T G:\test.csv.arff -p 1 -distribution > G:\out.txt
In the above example, first attribute is an an identifier (string). RemoveType filter will remove all string fields while building the model. However, you can still ask weka to include that identifier as part of the output (predictions) by passing as argument to -p. In my case first attribute (partner_id) is identifier so it gets listed in the output along with predictions. (-distribution option is to output prediction scores for all class labels). You can get more details from http://weka.wikispaces.com/Instance+ID
=== Predictions on test data ===
inst# actual predicted error distribution (partner_id)
1 1:? 2:0 0,*1 (8i7t3)
2 1:? 2:0 0,*1 (8i7u1)
3 1:? 2:0 0,*1 (8i7um)
4 1:? 2:0 0.1,*0.9 (8i7ux)
5 1:? 2:0 0,*1 (8i7va)
6 1:? 2:0 0,*1 (8i7vb)
7 1:? 2:0 0,*1 (8i7vf)
Hope you find this helpful..
For anyone coming to this question late, it is possible to do it in the GUI. Here is the answer I got from Mark Hall (from the Weka project):
The FilteredClassifier is available in the GUI or command line just
like any other classifier. Just configure it with your base classifier
and a Remove filter (to remove the ID etc. before the training/test
data is passed to the base classifier).
Elaborating on Nicholas' answer: if you want to do it from the GUI, in addition to selecting the FilteredClassifier, you should open "More options..." in the "Test options" box and enter the index of the identifier attribute into the "Output additional attributes" field. To enable this field, you have to tick the "Output predictions" box first.
In Weka 3.7, the additional attributes must be specified as a parameter of the chosen method for "Output predictions" by left-clicking on the field (e.g. PlainText).