How to use ETag in Azure Table Store

Question

This has been confusing me for awhile. According to Microsoft's documentation, the Azure Table Store uses the ETag to maintain optimistic concurrency. To my understanding, when I do this:

var operation = TableOperation.Merge(item);
CloudTable table = Client.GetTableReference(TableName);
await table.CreateIfNotExistsAsync().ConfigureAwait(false);
TableResult result = await table.ExecuteAsync(operation, token).ConfigureAwait(false);

the ETag field should be updated and returned with the table result. However, I don't see this field update when I test locally. According to the documentation, I can override it by setting ETag = "*" but this defeats the purpose of using the ETag system if I do it with every update operation. So then, how can I use this field properly to ensure that out-of-date entities do not overwrite newer data?

Answer 1

Your question leaves a few things unclear that make this hard to answer, but here is maybe a start that could help, or at least help clarify your problem. It would really help if you could clarify 2 pieces of info, what types of column rearrangements you need, and how you distinguish what indicates that a row needs to have this transformation.

I'm also wondering if instead of trying to manipulate your data in its current shape, if it not might be more practical to figure out how to change the shape of your data to better represent your data, perhaps using something like pivot_longer(), I don't know how this data will ultimately be used or what the actual values indicate, but it doesn't seem to be very tidy in its current form, and instead having a "longer" table might be more meaningful, but I'll still provide what I think is a solution to your listed problem.

This creates some example data that looks like it reflects yours in the example table.

ID=seq(1:10)
group=sample(1:2,10,replace=T)
Data=matrix(sample(1:10,80,replace=T),nrow=10,ncol=8)

DataFrame=data.frame('ID'=ID,'Group'=group,Data)

You then define the groups of columns that need to be kept together. I can't tell if there is an automated way for you to indicate which columns are grouped, but this might get bulky if done manually. Some more information on what your column names actually are, and how they are distributed in groups would help.

ColumnGroups=list('One'=c('X1','X2'),'Two'=c('X3','X4'),'Three'=c('X5','X6'),'Four'=c('X7','X8'))

You can then figure out which rows need to have rearranged done by using some conditional. Based on your example, I'm assuming when the group variable equals 2, then the rearranging needs to be done, which is what I've used here.

FlipRows=DataFrame$Group==2

You can then have R only apply the rearrangement needed to those rows that need it, and define the rearrangement based on the ordering of the different column groups. I know you ask for a general solution, but is hard to identify the general solution you need without knowing what types of column rearrangements you need. If it is always flipping two sets of consecutive column groups, that would be easier to define without having to type it all out. What I have done here would require you to manually type out the order of the different column groups that you would like the rows to be rearranged as. The SortedDataFrame object seems to be what you are looking for, but might not actually reflect your real data. I removed columns 1 and 2 in this operation since those are ID and group which you don't want overridden.

SortedDataFrame=DataFrame

SortedDataFrame[FlipRows,-c(1,2)]=DataFrame[FlipRows,c(ColumnGroups$Two,ColumnGroups$One,ColumnGroups$Four,ColumnGroups$Three)]

This solution won't work if you need to rearrange each row differently, but it is unclear if that is the case. Try to provide any of the other info requested here, and let me know where this solution doesn't work for you, and that.