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Causal Consistency and Read and Write Concerns

With MongoDB's causally consistent client sessions, different combinations of read and write concerns provide different causal consistency guarantees. When causal consistency is defined to imply durability, then the following table lists the specific guarantees provided by the various combinations:

Read Concern
Write Concern
Read own writes
Monotonic reads
Monotonic writes
Writes follow reads

If causal consistency implies durability, then, as seen from the table, only read operations with "majority" read concern and write operations with "majority" write concern can guarantee all four causal consistency guarantees. That is, causally consistent client sessions can only guarantee causal consistency for:

  • Read operations with "majority" read concern; i.e. the read operations that return data that has been acknowledged by a majority of the replica set members and is durable.
  • Write operations with "majority" write concern; i.e. the write operations that request acknowledgement that the operation has been applied to a majority of the replica set's voting members.

If causal consistency does not imply durability (i.e. writes may be rolled back), then write operations with { w: 1 } write concern can also provide causal consistency.

Note

The other combinations of read and write concerns may also satisfy all four causal consistency guarantees in some situations, but not necessarily in all situations.

The read concern "majority" and write concern "majority" ensure that the four causal consistency guarantees hold even in circumstances (such as with a network partition) where two members in a replica set transiently believe that they are the primary. And while both primaries can complete writes with { w: 1 } write concern, only one primary will be able to complete writes with "majority" write concern.

For example, consider a situation where a network partition divides a five member replica set:

Network partition: new primary elected on one side but old primary has not stepped down yet.
Example
With the above partition
  • Writes with "majority" write concern can complete on P new but cannot complete on P old.
  • Writes with { w: 1 } write concern can complete on either P old or P new. However, the writes to P old (as well as the writes replicated to S 1) roll back once these members regain communication with the rest of the replica set.
  • After a successful write with "majority" write concern on P new, causally consistent reads with "majority" read concern can observe the write on P new, S 2,and S 3. The reads can also observe the write on P old and S 1 once they can communicate with the rest of the replica set and sync from the other members of the replica set. Any writes made to P old and/or replicated to S 1 during the partition are rolled back.

To illustrate the read and write concern requirements, the following scenarios have a client issue a sequence of operations with various combination of read and write concerns to the replica set:

The use of read concern "majority" and write concern "majority" in a causally consistent session provides the following causal consistency guarantees:

Read own writes Monotonic reads Monotonic writes Writes follow reads

Note
Scenario 1 (Read Concern "majority" and Write Concern "majority")

During the transient period with two primaries, because only P new can fulfill writes with { w: "majority" } write concern, a client session can issue the following sequence of operations successfully:

Sequence
Example
1. Write 1 with write concern "majority" to P new
2. Read 1 with read concern "majority" to S 2
3. Write 2 with write concern "majority" to P new

4. Read 2 with read concern "majority" to S 3
For item A, update qty to 50.
Read item A.
For items with qty less than or equal to 50,
update restock to true.
Read item A.
State of data with two primaries using read concern majority and write concern majority
Read own writes
Read 1 reads data from S 2 that reflects a state after Write 1.
Read 2 reads data from S 1 that reflects a state after Write1 1 followed by Write 2.
Monotonic reads
Read 2 reads data from S 3 that reflects a state after Read 1.
Monotonic writes
Write 2 updates data on P new that reflects a state after Write 1.
Writes follow reads
Write 2 updates data on P new that reflects a state of the data after Read 1 (i.e. an earlier state reflects the data read by Read 1).
Note
Scenario 2 (Read Concern "majority" and Write Concern "majority")

Consider an alternative sequence where Read 1 with read concern "majority" routes to S 1:

Sequence
Example
1. Write 1 with write concern "majority" to P new
2. Read 1 with read concern "majority" to S 1
3. Write 2 with write concern "majority" to P new

4. Read 2 with with read concern "majority" to S 3
For item A, update qty to 50.
Read item A.
For items with qty less than or equal to 50,
update restock to true.
Read item A.

In this sequence, Read 1 cannot return until the majority commit point has advanced on P old. This cannot occur until P old and S 1 can communicate with the rest of the replica set; at which time, P old has stepped down (if not already), and the two members sync (including Write 1) from the other members of the replica set.

Read own writes
Read 1 reflects a state of data after Write1 1, albeit after the network partition has healed and the member has sync'ed from the other members of the replica set.
Read 2 reads data from S 3 that reflects a state after Write1 1 followed by Write 2.
Monotonic reads
Read 2 reads data from S 3 that reflects a state after Read 1 (i.e. an earlier state is reflected in the data read by Read 1).
Monotonic writes
Write 2 updates data on P new that reflects a state after Write 1.
Writes follow reads
Write 2 updates data on P new that reflects a state of the data after Read 1 (i.e. an earlier state reflects the data read by Read 1).

The use of read concern "majority" and write concern { w: 1 } in a causally consistent session provides the following causal consistency guarantees if causal consistency implies durability:

Read own writes Monotonic reads Monotonic writes Writes follow reads

If causal consistency does not imply durability:

Read own writes Monotonic reads Monotonic writes Writes follow reads

Note
Scenario 3 (Read Concern "majority" and Write Concern {w: 1})

During the transient period with two primaries, because both P old and P new can fulfill writes with { w: 1 } write concern, a client session could issue the following sequence of operations successfully but not be causally consistent if causal consistency implies durability:

Sequence
Example
1. Write 1 with write concern { w: 1 } to P old
2. Read 1 with read concern "majority" to S 2
3. Write 2 with write concern { w: 1 } to P new

4. Read 2 with with read concern "majority" to S 3
For item A, update qty to 50.
Read item A.
For items with qty less than or equal to 50,
update restock to true.
Read item A.
State of data with two primaries using read concern majority and write concern 1

In this sequence,

  • Read 1 cannot return until the majority commit point has advanced on P new past the time of Write 1.
  • Read 2 cannot return until the majority commit point has advanced on P new past the time of Write 2.
  • Write 1 will roll back when the network partition is healed.

If causal consistency implies durability

Read own writes
Read 1 reads data from S 2 that does not reflect a state after Write 1.
Monotonic reads
Read 2 reads data from S 3 that reflects a state after Read 1 (i.e. an earlier state is reflected in the data read by Read 1).
Monotonic writes
Write 2 updates data on P new that does not reflect a state after Write 1.
Writes follow reads
Write 2 updates data on P new that reflects a state after Read 1 (i.e. an earlier state reflects the data read by Read 1).

If causal consistency does not imply durability

Read own writes
Read 1 reads data from S 2 returns data that reflects a state equivalent to Write 1 followed by rollback of Write 1.
Monotonic reads
Read 2 reads data from S 3 that reflects a state after Read 1 (i.e. an earlier state is reflected in the data read by Read 1).
Monotonic writes
Write 2 updates data on P new that is equivalent to after Write 1 followed by rollback of Write 1.
Writes follow reads
Write 2 updates data on P new that reflects a state after Read 1 (i.e. whose earlier state reflects the data read by Read 1).
Note
Scenario 4 (Read Concern "majority" and Write Concern {w: 1})

Consider an alternative sequence where Read 1 with read concern "majority" routes to S 1:

Sequence
Example
1. Write 1 with write concern { w: 1 } to P old
2. Read 1 with read concern "majority" to S 1
3. Write 2 with write concern { w: 1 } to P new

4. Read 2 with with read concern "majority" to S 3
For item A, update qty to 50.
Read item A.
For items with qty less than or equal to 50,
update restock to true.
Read item A.

In this sequence:

  • Read 1 cannot return until the majority commit point has advanced on S 1. This cannot occur until P old and S 1 can communicate with the rest of the replica set. At which time, P old has stepped down (if not already), Write 1 is rolled back from P old and S 1, and the two members sync from the other members of the replica set.

If causal consistency implies durability

Read own writes
The data read by Read 1 does not reflect the results of Write 1, which has rolled back.
Monotonic reads
Read 2 reads data from S 3 that reflects a state after Read 1 (i.e. whose earlier state reflects the data read by Read 1).
Monotonic writes
Write 2 updates data on P new that does not reflect a state after Write 1, which had preceded Write 2 but has rolled back.
Writes follow reads
Write 2 updates data on P new that reflects a state after Read 1 (i.e. whose earlier state reflects the data read by Read 1).

If causal consistency does not imply durability

Read own writes
Read 1 returns data that reflects the final result of Write 1 since Write 1 ultimately rolls back.
Monotonic reads
Read 2 reads data from S 3 that reflects a state after Read 1 (i.e. an earlier state reflects the data read by Read 1).
Monotonic writes
Write 2 updates data on P new that is equivalent to after Write 1 followed by rollback of Write 1.
Writes follow reads
Write 2 updates data on P new that reflects a state after Read 1 (i.e. an earlier state reflects the data read by Read 1).

The use of read concern "local" and write concern { w: 1 } in a causally consistent session cannot guarantee causal consistency.

Read own writes Monotonic reads Monotonic writes Writes follow reads

This combination may satisfy all four causal consistency guarantees in some situations, but not necessarily in all situations.

Note
Scenario 5 (Read Concern "local" and Write Concern {w: 1})

During this transient period, because both P old and P new can fulfill writes with { w: 1 } write concern, a client session could issue the following sequence of operations successfully but not be causally consistent:

Sequence
Example
1. Write 1 with write concern { w: 1 } to P old
2. Read 1 with read concern "local" to S 1
3. Write 2 with write concern { w: 1 } to P new

4. Read 2 with read concern "local" to S 3
For item A, update qty to 50.
Read item A.
For items with qty less than or equal to 50,
update restock to true.
Read item A.
State of data with two primaries using read concern local and write concern 1
Read own writes
Read 2 reads data from S 3 that only reflects a state after Write 2 and not Write 1 followed by Write 2.
Monotonic reads
Read 2 reads data from S 3 that does not reflect a state after Read 1 (i.e. an earlier state does not reflect the data read by Read 1).
Monotonic writes
Write 2 updates data on P new that does not reflect a state after Write 1.
Write follow read
Write 2 updates data on P new that does not reflect a state after Read 1 (i.e. an earlier state does not reflect the data read by Read 1).

The use of read concern "local" and write concern "majority" in a causally consistent session provides the following causal consistency guarantees:

Read own writes Monotonic reads Monotonic writes Writes follow reads

This combination may satisfy all four causal consistency guarantees in some situations, but not necessarily in all situations.

Note
Scenario 6 (Read Concern "local" and Write Concern "majority")

During this transient period, because only P new can fulfill writes with { w: "majority" } write concern, a client session could issue the following sequence of operations successfully but not be causally consistent:

Sequence
Example
1. Write 1 with write concern "majority" to P new
2. Read 1 with read concern "local" to S 1
3. Write 2 with write concern "majority" to P new

4. Read 2 with read concern "local" to S 3
For item A, update qty to 50.
Read item A.
For items with qty less than or equal to 50,
update restock to true.
Read item A.
State of data with two primaries using read concern local and write concern majority
Read own writes.
Read 1 reads data from S 1 that does not reflect a state after Write1 1.
Monotonic reads.
Read 2 reads data from S 3 that does not reflect a state after Read 1 (i.e. an earlier state does not reflect the data read by Read 1).
Monotonic writes
Write 2 updates data on P new that reflects a state after Write 1.
Write follow read.
Write 2 updates data on P new that does not reflect a state after Read 1 (i.e. an earlier state does not reflect the data read by Read 1).
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