When a deletion query is executed in couchbase it flags the resulting documents for deletion.
https://developer.couchbase.com/documentation/server/3.x/developer/dev-guide-3.0/delete-info.html
Is there a way to stop the process and remove this flag?
Related
What will be suggested approach for archiving couchbase documents based on certain criteria to secondary DB considering secondary cluster is also couchbase.
After moving those document to secondary cluster it should be deleted from primary database that is the requirement.
What will efficient approach to move millions of documents to other couchbase cluster (secondary) and then delete from primary database.
If you want the archiving to be continuous, you could configure Cross Data Center Replication (XDCR) to the secondary cluster, with a filter that ignores document expiry and deletion.
Specifically, enable:
Do not replicate document expirations
Remove TTL from replicated items
Do not replicate DELETE operations
Then set a max-TTL on the bucket in the source cluster so the documents there expire automatically. Alternatively, delete documents from the source cluster on your own schedule.
CAVEAT: You'll want to keep a close eye on the XDCR status to make sure documents are replicated before they are deleted/expired.
When setting up a file-based sync in Data Connection, I see there are a few different options for 'Transaction Type'. What's the difference between them? When might I use them?
From the Foundry docs:
Transaction types
The way dataset files are modified in a transaction depends on the transaction type. There are four possible transaction types: SNAPSHOT, APPEND, UPDATE, and DELETE.
SNAPSHOT
A SNAPSHOT transaction replaces the current view of the dataset with a completely new set of files.
SNAPSHOT transactions are the simplest transaction type, and are the basis of batch pipelines.
APPEND
An APPEND transaction adds new files to the current dataset view.
An APPEND transaction cannot modify existing files in the current dataset view. If an APPEND transaction is opened and existing files are overwritten, then attempting to commit the transaction will fail.
APPEND transactions are the basis of incremental pipelines. By only syncing new data into Foundry and only processing this new data throughout the pipeline, changes to large datasets can be processed end-to-end in a performant way. However, building and maintaining incremental pipelines comes with additional complexity. Learn more about incremental pipelines.
UPDATE
An UPDATE transaction, like an APPEND, adds new files to a dataset view, but may also overwrite the contents of existing files.
DELETE
A DELETE transaction removes files that are in the current dataset view.
Note that committing a DELETE transaction does not delete the underlying file from the backing file system—it simply removes the file reference from the dataset view.
In practice, DELETE transactions are mostly used to enable data retention workflows. By deleting files on a dataset based on a retention policy—typically based on the age of the file—data can be removed from Foundry, both to minimize storage costs and to comply with data governance requirements.
Data Connection doesn't let you create a sync with a DELETE transaction type, because a sync that purely deletes data doesn't really make sense! If you'd like to delete data from your sync'd dataset, you can use a SNAPSHOT transaction to do so, but note that previous versions of the dataset will still include those files.
You can combine an APPEND or UPDATE transaction type with file-based sync filters to only ingest the newly changed files on each run of your sync.
I am new to couchbase.
i had lot of duplicate records in my bucket.
i tried to delete the repeating records but accidentally deleted all records.
i dont know how to retrieve the deleted records.
pls help me to get back the records or guide me to change the bucket to previous state
I don't think that is possible if you don't have a dump of your data...
Couchbase does not immediately erase the data from deleted documents. Instead, deleted documents are marked, and the space is later reclaimed. If the reclamation has not yet happened, it may be possible for you to manually recover the deleted documents from the underlying files. Shut down your server immediately though, so the reclamation doesn't happen inadvertently.
This article is a place to start:
https://blog.avira.com/recovering-couchbase-data-vbuckets/
I'm new to couchbase and was wondering if very frequent updates to a single document (possibly every second) will cause all updates to pass through the disk write queue, or only the last update made to the document?
In other words, does couchbase optimize disk writes by only writing the document to disk once, even if updated multiple time between writes.
Based on the docs, http://docs.couchbase.com/admin/admin/Monitoring/monitor-diskqueue.html, it sounds like all updates are processed. If anyone can confirm this, I'd be grateful.
thanks
Updates are held in a disk queue before being written to disk. If a write to a document occurs and a previous write is still in the disk queue, then the two writes will be coalesced, and only the more recent version will actually be written to disk.
Exactly how fast the disk queue drains will depend on the storage subsystem, so whether writes to the same key get coalesced will depend on how quick the writes come in compared to the storage subsystem speed / node load.
Jako, you should worry more about updates happening in the millisecond time frame or more than one update happening in 1 (one) millisecond. The disc write isn't the problem, Couchbase solves this intelligently itself but the fact that you will concurrency issues when you operate in the milliseconds time frame.
I've run into them fairly easily when I tested my application and first couldn't understand why Node.js (in my case) sometimes would write data to CouchBase and sometimes not. If it didn't write to CouchBase usually for the first record.
More problems raised when I first checked if a document with a specific key existed, upon not existing I would try to write it to CouchBase only to find out that in the meantime an early callback had finished and now there was indeed a key for the same document.
In those case you have to operate with the CAS flag and program it iteratively so that your app is continuously trying to pull the right document for that key and then updates. Keep this in mind especially when running tests and updates to the same document is being done!
I have 3 nodes in Couchbase cluster with number of replicas set to 1.
While performing a multithreaded insert of 1M documents, I restart one of the nodes couple of times.
The result is that at the end of insert operations, I am missing about 15% of the data.
Any idea how to prevent the data loss?
Firstly, did you failover the node when it went out of the cluster? Until you failover, the replica on the other nodes will not be promoted to active (and hence any replica data will not be accessible).
Secondly, are you checking the return value from your insert operations? If a node is inaccessible (but before a failover) operations will return an exception (likely "timeout") - you should ensure the application retries the insert.
Thirdly, by default most CRUD operations on Couchbase return as soon as the update has occurred on the master node for maximum performance. As a consequence if you do loose a node it's possible that the replica hasn't been written yet - so there would be no replica even if you did perform a failover. To prevent this you can use the observe operation to not report the operation "complete" until a replica node has a copy - see Monitoring Items using observe.
Note that using observe will result in a performance penalty, but this may be an acceptable tradeoff for modifications you particularly care about.