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https://issues.apache.org/jira/browse/CASSANDRA-8844?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15243142#comment-15243142
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Branimir Lambov commented on CASSANDRA-8844:
--------------------------------------------
Some confusion in the read / replay part, probably my fault for not documenting
the details well.
Replay positions (or CLSP) are given as a segment id, and uncompressed (or
"logical" as Jason calls it) position within the segment file. For Cassandra
2.2+ logical position does not have to match file position. When replaying,
anything with greater segment id, or with equal segment id but greater-or-equal
logical position, must be replayed.
The following are potential problems with that:
- [Descriptor parsed id mismatch
error|https://github.com/apache/cassandra/compare/trunk...josh-mckenzie:8844_review#diff-9fe0bd988c4fc47a022f589f5ad72b09R148]
doesn't look right. The replay position specifies from which id (and position
within that id) we should replay. In addition to (parts of) the file with the
same id, this includes all files with higher ids. Mismatch is normal.
- [Mutation before offset
check|https://github.com/apache/cassandra/compare/trunk...josh-mckenzie:8844_review#diff-9fe0bd988c4fc47a022f589f5ad72b09R246]
compares file position with logical segment position and is only valid for
uncompressed files.
- [{{shouldSkipSegment}}
JavaDoc|https://github.com/apache/cassandra/compare/trunk...josh-mckenzie:8844_review#diff-0184f4e288c68732ceb30cdc49a76c4aR73]
should make it clear which kind of position it needs (it is used correctly).
- It's not a good thing that these weren't caught by tests.
Other remarks:
-
[{{prepReader}}|https://github.com/apache/cassandra/compare/trunk...josh-mckenzie:8844_review#diff-9fe0bd988c4fc47a022f589f5ad72b09R108]
is only called for pre-2.1 segments. JavaDoc does not say so. I don't think we
want this in the handler interface, inline it at its one use site.
-
[{{statusTracker.flagError}}|https://github.com/apache/cassandra/compare/trunk...josh-mckenzie:8844_review#diff-9fe0bd988c4fc47a022f589f5ad72b09R270]
isn't a very fitting name for what is actually a termination request.
- [{{flagError}} and
return|https://github.com/apache/cassandra/compare/trunk...josh-mckenzie:8844_review#diff-9fe0bd988c4fc47a022f589f5ad72b09R305]
is inconsistent with the rest in {{readSection}}. It should also return
regardless of the shouldStop result as there's nothing meaningful to be done
with the rest of the section.
The old code does this differently, always breaks sync _and_ segment replay on
errors, which AFAIR is done to make certain we don't try to replay old data in
a partially overwritten pre-2.2 segment. Such data should have an invalid sync
marker, though, so this change is fine, and should be an improvement as it
could be able to scavenge more on bit rot. In the common file-not-fully-written
case, though, you will get a second error due to this change when it tries to
read the next section.
Pre-existing issues:
-
[segmentId|https://github.com/apache/cassandra/compare/trunk...josh-mckenzie:8844_review#diff-9fe0bd988c4fc47a022f589f5ad72b09R120]
confuses that it would be the one used later. We should rename this to
{{segmentIdFromFilename}}.
- [tolerateErrorsInSection
&=|https://github.com/apache/cassandra/compare/trunk...josh-mckenzie:8844_review#diff-9fe0bd988c4fc47a022f589f5ad72b09R186]:
I don't think it was intended for the value to depend on previous iterations.
> Change Data Capture (CDC)
> -------------------------
>
> Key: CASSANDRA-8844
> URL: https://issues.apache.org/jira/browse/CASSANDRA-8844
> Project: Cassandra
> Issue Type: New Feature
> Components: Coordination, Local Write-Read Paths
> Reporter: Tupshin Harper
> Assignee: Joshua McKenzie
> Priority: Critical
> Fix For: 3.x
>
>
> "In databases, change data capture (CDC) is a set of software design patterns
> used to determine (and track) the data that has changed so that action can be
> taken using the changed data. Also, Change data capture (CDC) is an approach
> to data integration that is based on the identification, capture and delivery
> of the changes made to enterprise data sources."
> -Wikipedia
> As Cassandra is increasingly being used as the Source of Record (SoR) for
> mission critical data in large enterprises, it is increasingly being called
> upon to act as the central hub of traffic and data flow to other systems. In
> order to try to address the general need, we (cc [~brianmhess]), propose
> implementing a simple data logging mechanism to enable per-table CDC patterns.
> h2. The goals:
> # Use CQL as the primary ingestion mechanism, in order to leverage its
> Consistency Level semantics, and in order to treat it as the single
> reliable/durable SoR for the data.
> # To provide a mechanism for implementing good and reliable
> (deliver-at-least-once with possible mechanisms for deliver-exactly-once )
> continuous semi-realtime feeds of mutations going into a Cassandra cluster.
> # To eliminate the developmental and operational burden of users so that they
> don't have to do dual writes to other systems.
> # For users that are currently doing batch export from a Cassandra system,
> give them the opportunity to make that realtime with a minimum of coding.
> h2. The mechanism:
> We propose a durable logging mechanism that functions similar to a commitlog,
> with the following nuances:
> - Takes place on every node, not just the coordinator, so RF number of copies
> are logged.
> - Separate log per table.
> - Per-table configuration. Only tables that are specified as CDC_LOG would do
> any logging.
> - Per DC. We are trying to keep the complexity to a minimum to make this an
> easy enhancement, but most likely use cases would prefer to only implement
> CDC logging in one (or a subset) of the DCs that are being replicated to
> - In the critical path of ConsistencyLevel acknowledgment. Just as with the
> commitlog, failure to write to the CDC log should fail that node's write. If
> that means the requested consistency level was not met, then clients *should*
> experience UnavailableExceptions.
> - Be written in a Row-centric manner such that it is easy for consumers to
> reconstitute rows atomically.
> - Written in a simple format designed to be consumed *directly* by daemons
> written in non JVM languages
> h2. Nice-to-haves
> I strongly suspect that the following features will be asked for, but I also
> believe that they can be deferred for a subsequent release, and to guage
> actual interest.
> - Multiple logs per table. This would make it easy to have multiple
> "subscribers" to a single table's changes. A workaround would be to create a
> forking daemon listener, but that's not a great answer.
> - Log filtering. Being able to apply filters, including UDF-based filters
> would make Casandra a much more versatile feeder into other systems, and
> again, reduce complexity that would otherwise need to be built into the
> daemons.
> h2. Format and Consumption
> - Cassandra would only write to the CDC log, and never delete from it.
> - Cleaning up consumed logfiles would be the client daemon's responibility
> - Logfile size should probably be configurable.
> - Logfiles should be named with a predictable naming schema, making it
> triivial to process them in order.
> - Daemons should be able to checkpoint their work, and resume from where they
> left off. This means they would have to leave some file artifact in the CDC
> log's directory.
> - A sophisticated daemon should be able to be written that could
> -- Catch up, in written-order, even when it is multiple logfiles behind in
> processing
> -- Be able to continuously "tail" the most recent logfile and get
> low-latency(ms?) access to the data as it is written.
> h2. Alternate approach
> In order to make consuming a change log easy and efficient to do with low
> latency, the following could supplement the approach outlined above
> - Instead of writing to a logfile, by default, Cassandra could expose a
> socket for a daemon to connect to, and from which it could pull each row.
> - Cassandra would have a limited buffer for storing rows, should the listener
> become backlogged, but it would immediately spill to disk in that case, never
> incurring large in-memory costs.
> h2. Additional consumption possibility
> With all of the above, still relevant:
> - instead (or in addition to) using the other logging mechanisms, use CQL
> transport itself as a logger.
> - Extend the CQL protoocol slightly so that rows of data can be return to a
> listener that didn't explicit make a query, but instead registered itself
> with Cassandra as a listener for a particular event type, and in this case,
> the event type would be anything that would otherwise go to a CDC log.
> - If there is no listener for the event type associated with that log, or if
> that listener gets backlogged, the rows will again spill to the persistent
> storage.
> h2. Possible Syntax
> {code:sql}
> CREATE TABLE ... WITH CDC LOG
> {code}
> Pros: No syntax extesions
> Cons: doesn't make it easy to capture the various permutations (i'm happy to
> be proven wrong) of per-dc logging. also, the hypothetical multiple logs per
> table would break this
> {code:sql}
> CREATE CDC_LOG mylog ON mytable WHERE MyUdf(mycol1, mycol2) = 5 with
> DCs={'dc1','dc3'}
> {code}
> Pros: Expressive and allows for easy DDL management of all aspects of CDC
> Cons: Syntax additions. Added complexity, partly for features that might not
> be implemented
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