one misconception of mongos read concern: majority is that it guarantees read-your-write consistency by reading from a majority of nodes. this is a common misunderstanding because it’s counterpart write concern: majority requires acks from the majority of nodes.
… but that’s not at all what read concern does!
reads always get submitted to a single node using a server selection process that takes into account your read preference (primary, primaryPreferred, secondary, etc).
- if you have a primary read preference, a read will always go to the primary.
- if you have a secondary read preference, a read will get submitted to a single secondary. if you have two replicas, a read goes to one of them
when the read concern (not the same as read preference, great naming mongodb) is set to majority, that’s basically saying “only return data for this query that has been committed / successfully written to the majority of nodes”.
this does not mean that you’re always reading the latest write
to understand this, you need to understand mongo’s notion of a “majority commit”.
the majority commit value for any write is determined by the primary during the standard replication process. when data gets replicated to a secondary node, it’ll check with the primary whether to update it’s “majority commit” snapshot of the data. If that value has not been majority committed, the majority commit snapshot will maintain its previous majority committed value.
that’s why it’s still possible to read stale values with read: majority. The majority commit snapshot on any given node is only updated for a particular value when it is actually successfully replicated from the primary to the majority of its secondary nodes. so the node you’re reading from may not have the majority-committed version of the data you literally just wrote. it’ll give you the previous majority committed value, instead of the latest value that perhaps has not yet propagated to the majority of nodes.
errr so what’s the point even MONGO
what it does mean is that you can trust that the data you’re reading has a high level of durability because in the event of a failure the value you’re reading is unlikely to be rolled back since it’s been majority committed.
read your own writes for real
reading your own writes is a special case of causal consistency and while having a majority read concern is not sufficient, it is a necessary component of setting up read your own write consistency in mongo.
to achieve reading your own writes, you need to ensure the following mAgiCaL settings:
- operations are done inside a session with causal consistency enabled
- write concern is majority
- read concern is majority
- lol?
why do you need to set specific read and write concerns even though causal consistency is enabled? I’m not sure, but it’s an extremely confusing and misleading API
theoretically/formally speaking… causal consistency includes read your own writes consistency, but in MongoDB enabling causal consistency is not sufficient for reading your own writes!
if you do have these settings on, MongoDB will track operations with a global logical clock and your reads will block until it’s able to read the most recent majority committed write from the same session.
without causal consistency enabled, a write may go to a majority of nodes but the read may still would up returning non-majority-committed data from a node that does not have the write that just happened in the same session. The causal consistency session is what causes reads to block if it attempts to read a stale write.
wow this sounds painful what are my other options
situations involving multi-document operations are most likely going to bring up requirements around read/write consistency. the best way to skip all that is to use mongo / nosql as it was designed and focus on single document, atomic operations that do not require you to interleave read and writes. this means modeling your data in a de-normalized way and not treat mongo too much like a relational db. it’s actually what they recommend too!
OR just dont use mongo. postgresql4lyfe
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