[jira] [Comment Edited] (CASSANDRA-8844) Change Data Capture (CDC)
[ https://issues.apache.org/jira/browse/CASSANDRA-8844?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15158608#comment-15158608 ] Bill de hOra edited comment on CASSANDRA-8844 at 2/23/16 9:21 AM: -- In the current design doc it says bq. Matches replication strategy Does this mean if RF was say, three, that three CDC commit logs would be written to across the cluster (compared to say, one write at the coordinator)? In turn I guess that means systems consuming the capture logs will have to perform some kind of de-duplication as de-duplication's not in scope for the design. was (Author: dehora): In the current design doc it says bq. Matches replication strategy Does this mean if RF was say, three, that three CDC commit logs being written to across the cluster and not just say, at the coordinator? In turn I guess that means systems consuming the capture logs will have to perform some kind of de-duplication as de-duplication's not in scope for the design. > 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
[jira] [Commented] (CASSANDRA-8844) Change Data Capture (CDC)
[ https://issues.apache.org/jira/browse/CASSANDRA-8844?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15158608#comment-15158608 ] Bill de hOra commented on CASSANDRA-8844: - In the current design doc it says bq. Matches replication strategy Does this means if RF was say, three, that three CDC commit logs being written to across the cluster and not just say, at the coordinator? In turn I guess that means systems consuming the capture logs will have to perform some kind of de-duplication as de-duplication's not in scope for the design. > 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
[jira] [Comment Edited] (CASSANDRA-8844) Change Data Capture (CDC)
[ https://issues.apache.org/jira/browse/CASSANDRA-8844?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15158608#comment-15158608 ] Bill de hOra edited comment on CASSANDRA-8844 at 2/23/16 9:20 AM: -- In the current design doc it says bq. Matches replication strategy Does this mean if RF was say, three, that three CDC commit logs being written to across the cluster and not just say, at the coordinator? In turn I guess that means systems consuming the capture logs will have to perform some kind of de-duplication as de-duplication's not in scope for the design. was (Author: dehora): In the current design doc it says bq. Matches replication strategy Does this means if RF was say, three, that three CDC commit logs being written to across the cluster and not just say, at the coordinator? In turn I guess that means systems consuming the capture logs will have to perform some kind of de-duplication as de-duplication's not in scope for the design. > 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
[jira] [Created] (CASSANDRA-2837) Setting RR Chance via CliClient results in chance being too low
Setting RR Chance via CliClient results in chance being too low
Key: CASSANDRA-2837
URL: https://issues.apache.org/jira/browse/CASSANDRA-2837
Project: Cassandra
Issue Type: Bug
Affects Versions: 0.7.6
Reporter: Bill de hOra
running a command like
{noformat}
update column family shorturls with read_repair_chance=0.4;
{noformat}
results in the value being set to 0.0040.
Affects 0.7.6.-2; seems to be fixed on trunk/0.8.
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[jira] [Updated] (CASSANDRA-2837) Setting RR Chance via CliClient results in chance being too low
[
https://issues.apache.org/jira/browse/CASSANDRA-2837?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Bill de hOra updated CASSANDRA-2837:
Description:
running a command like
{noformat}
update column family shorturls with read_repair_chance=0.4;
{noformat}
results in the value being set to 0.0040. Was expecting it to be 0.4.
Affects 0.7.6.-2; seems to be fixed on trunk/0.8.
was:
running a command like
{noformat}
update column family shorturls with read_repair_chance=0.4;
{noformat}
results in the value being set to 0.0040.
Affects 0.7.6.-2; seems to be fixed on trunk/0.8.
Assignee: (was: Jon Hermes)
Setting RR Chance via CliClient results in chance being too low
Key: CASSANDRA-2837
URL: https://issues.apache.org/jira/browse/CASSANDRA-2837
Project: Cassandra
Issue Type: Bug
Affects Versions: 0.7.6
Reporter: Bill de hOra
running a command like
{noformat}
update column family shorturls with read_repair_chance=0.4;
{noformat}
results in the value being set to 0.0040. Was expecting it to be 0.4.
Affects 0.7.6.-2; seems to be fixed on trunk/0.8.
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For more information on JIRA, see: http://www.atlassian.com/software/jira
