In the CassandraStorage, remove repair run table scans #105
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…nc break-down of per cluster run-throughs of known run IDs. ref: #105
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| return repairRuns; | ||
| return getClusters().stream() | ||
| // Grab all ids for the given cluster name | ||
| .map((cluster) -> getRepairRunIdsForCluster(cluster.getName())) |
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| // Grab repair runs asynchronously for all the ids returned by the index table | ||
| .flatMap((Collection<UUID> repairRunIds) | ||
| -> repairRunIds.stream() | ||
| .map((repairRunId) -> session.executeAsync(getRepairRunPrepStmt.bind(repairRunId)))) |
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…nc break-down of per cluster run-throughs of known run IDs. ref: #105
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…nc break-down of per cluster run-throughs of known run IDs. ref: #105
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* Cassandra performance: Replace sequence ids with time-based UUIDs Makes the schema changes in a separate migration step, so that data in the repair_unit and repair_schedule tables can be migrated over. ref: - #99 - #94 - #99 (comment) * Simplify the creation of repair runs and their segments. Repair runs and their segments are one unit of work in concept and the persistence layer should be designed accordingly. Previous they were separated because the concern of sequence generation for IDs were exposed in the code. This is now encapsulated within storage implementations. This work allows the CassandraStorage to implement segments as clustering keys within the repair_run table. ref: - #94 - #101 * In CassandraStorage implement segments as clustering keys within the repair_run table. Change required in IStorage so to identify a segment both by runId and segmentId. ref: - #94 - #102 * Fix number of parallel repair computation Downgrade to Dropwizard 1.0.7 and Guava 19.0 to fix dependency issues Make repair manager schedule cycle configurable (was 30s hardcoded) ref: #108 * In CassandraStorage replace the table scan on `repair_run` with a async break-down of per cluster run-throughs of known run IDs. ref: #105
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* Cassandra performance: Replace sequence ids with time-based UUIDs Makes the schema changes in a separate migration step, so that data in the repair_unit and repair_schedule tables can be migrated over. ref: - #99 - #94 - #99 (comment) * Simplify the creation of repair runs and their segments. Repair runs and their segments are one unit of work in concept and the persistence layer should be designed accordingly. Previous they were separated because the concern of sequence generation for IDs were exposed in the code. This is now encapsulated within storage implementations. This work allows the CassandraStorage to implement segments as clustering keys within the repair_run table. ref: - #94 - #101 * In CassandraStorage implement segments as clustering keys within the repair_run table. Change required in IStorage so to identify a segment both by runId and segmentId. ref: - #94 - #102 * Fix number of parallel repair computation Downgrade to Dropwizard 1.0.7 and Guava 19.0 to fix dependency issues Make repair manager schedule cycle configurable (was 30s hardcoded) ref: #108 * In CassandraStorage replace the table scan on `repair_run` with a async break-down of per cluster run-throughs of known run IDs. ref: #105
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In CassandraStorage replace the table scan on
repair_runwith a async break-down of per cluster run-throughs of known run IDs.