The central idea of incremental repair is to allow repair participants
to select and repair only a portion of the dataset to speed up the
repair process. All repair participants must utilize an identical
selection method to repair and synchronize the same selected dataset.
There are two primary selection methods: time-based and file-based. The
time-based method selects data within a specified time frame. It is
versatile but it is less efficient because it requires reading all of
the dataset and omitting data beyond the time frame. The file-based
method selects data from unrepaired SSTables and is more efficient
because it allows the entire SSTable to be omitted. This document patch
implements the file-based selection method.
Incremental repair will only be supported for tablet tables; it will not
be supported for vnode tables. On one hand, the legacy vnode is less
important to support. On the other hand, the incremental repair for
vnode is much harder to implement. With vnodes, a SSTalbe could contain
data for multiple vnode ranges. When a given vnode range is repaired,
only a portion of the SSTable is repaired. This complicates the
manipulation of SSTables significantly during both repair and
compaction. With tablets, an entire tablet is repaired so that a
sstable is either fully repaired or not repaired which is a huge
simplification.
This patch uses the repaired_at from sstables::statistics component to
mark a sstable as repaired. It uses a virtual clock as the repair
timestamp, i.e., using a monotonically increasing number for the
repaired_at field of a SSTable and sstables_repaired_at column in
system.tablets table. Notice that when a sstable is not repaired, the
repaired_at field will be set to the default value 0 by default. The
being_repaired in memory field of a SSTable is used to explicitly mark
that a SSTable is being selected. The following variables are used for
incremental repair:
The repaired_at on disk field of a SSTable is used.
- A 64-bit number increases sequentially
The sstables_repaired_at is added to the system.tablets table.
- repaired_at <= sstables_repaired_at means the sstable is repaired
The being_repaired in memory field of a SSTable is added.
- A repair UUID tells which sstable has participated in the repair
Initial test results:
1) Medium dataset results
Node amount: 3
Instance type: i4i.2xlarge
Disk usage per node: ~500GB
Cluster pre-populated with ~500GB of data before starting repairs job.
Results for Repair Timings:
The regular repair run took 210 mins.
Incremental repair 1st run took 183 mins, 2nd and 3rd runs took around 48s
The speedup is: 183 mins / 48s = 228X
2) Small dataset results
Node amount: 3
Instance type: i4i.2xlarge
Disk usage per node: ~167GB
Cluster pre-populated with ~167GB of data before starting the repairs job.
Regular repair 1st run took 110s, 2nd and 3rd runs took 110s.
Incremental repair 1st run took 110 seconds, 2nd and 3rd run took 1.5 seconds.
The speedup is: 110s / 1.5s = 73X
3) Large dataset results
Node amount: 6
Instance type: i4i.2xlarge, 3 racks
50% of base load, 50% read/write
Dataset == Sum of data on each node
Dataset Non-incremental repair (minutes)
1.3 TiB 31:07
3.5 TiB 25:10
5.0 TiB 19:03
6.3 TiB 31:42
Dataset Incremental repair (minutes)
1.3 TiB 24:32
3.0 TiB 13:06
4.0 TiB 5:23
4.8 TiB 7:14
5.6 TiB 3:58
6.3 TiB 7:33
7.0 TiB 6:55
Fixes#22472Closesscylladb/scylladb#24291
* github.com:scylladb/scylladb:
replica: Introduce get_compaction_reenablers_and_lock_holders_for_repair
compaction: Move compaction_reenabler to compaction_reenabler.hh
topology_coordinator: Make rpc::remote_verb_error to warning level
repair: Add metrics for sstable bytes read and skipped from sstables
test.py: Disable incremental for test_tombstone_gc_for_streaming_and_repair
test.py: Add tests for tablet incremental repair
repair: Add tablet incremental repair support
compaction: Add tablet incremental repair support
feature_service: Add TABLET_INCREMENTAL_REPAIR feature
tablet_allocator: Add tablet_force_tablet_count_increase and decrease
repair: Add incremental helpers
sstable: Add being_repaired to sstable
sstables: Add set_repaired_at to metadata_collector
mutation_compactor: Introduce add operator to compaction_stats
tablet: Add sstables_repaired_at to system.tablets table
test: Fix drain api in task_manager_client.py
The feature is supported by all live versions since
version 5.4 / 2024.1.
(Although up to 6da758d74c
it could be disabled using the config option)
Signed-off-by: Benny Halevy <bhalevy@scylladb.com>
When repairing a partition with many rows, we can store many fragments in a repair_row_on_wire object which is sent as a rpc stream message.
This could cause reactor stalls when the rpc stream compression is turned on, because the compression compresses the whole message without any split and compression.
This patch solves the problem at the higher level by reducing the message size that is sent to the rpc stream.
Tests are added to make sure the message split works.
Fixes#24808Closesscylladb/scylladb#25002
* github.com:scylladb/scylladb:
repair: Avoid too many fragments in a single repair_row_on_wire
repair: Change partition_key_and_mutation_fragments to use chunked_vector
utils: Allow chunked_vector::erase to work with non-default-constructible type
When repairing a partition with many rows, we can store many fragments
in a repair_row_on_wire object which is sent as a rpc stream message.
This could cause reactor stalls when the rpc stream compression is
turned on, because the compression compresses the whole message without
any split and compression.
This patch solves the problem at the higher level by reducing the
message size that is sent to the rpc stream.
Tests are added to make sure the message split works.
Fixes#24808
Nowadays the way to configure an internal service is
1. service declares its config struct
2. caller (main/test/tool) fills the respective config with values it wants
3. the service is started with the config passed by value
The feature service code behaves likewise, but provides a helper method to create its config out of db::config. This PR moves this helper out of gms code, so that it doesn't mess with system-wide db::config and only needs its own small struct feature_config.
For the reference: similar changes with other services: #23705 , #20174 , #19166Closesscylladb/scylladb#25118
* github.com:scylladb/scylladb:
gms,init: Move get_disabled_features_from_db_config() from gms
code: Update callers generating feature service config
gms: Make feature_config a simple struct
gms: Split feature_config_from_db_config() into two
Now when all callers are decoupled from gms config generating code, the
latter can be decoupled from the db::config.
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
All config-s out there are plan structures without private members and
methods used to simply carry the set of config values around. Make the
feature service config alike.
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
The helper in question generates the disabled features set and assigns
one on the config. This patch detaches the features set generation into
an other function. The former will go away eventually and the latter
will be kept around main/test code.
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
When allocating tablets for a new table, add the option to create a
co-located tablet map with an existing base table.
The co-located tablet map is created with the base_table value set.
* The new abort command explicitly represents the abortion flow in
mutation streaming, clearly identifying operations that are
intentionally aborted. This reduces ambiguity around failures in
streaming operations.
* In the error-handling section, aborted operations are now
explicitly marked as the cause of the streaming failure. This allows
us to differentiate them from genuine errors and appropriately adjust
log severity to reduce unnecessary alarm caused by aborted streaming
failures.
* To avoid alarming users with excessive error logs, log severity for
streaming failures caused by aborted operations has been downgraded.
This helps keep logs cleaner and prevents unnecessary concerns.
* A new feature has been added to ensure mixed clusters during updates
do not receive unsupported RPC messages, improving compatibility and
stability.
fixes: https://github.com/scylladb/scylladb/issues/23076Closesscylladb/scylladb#23214
Currently, the system.compaction_history table miss precious
information like the type of compaction (cleanup, major, resharding,
etc) or the sstable generations involved (in and out) used countless
times to diagnose issues.
Thus, the commit extend the current definition of the table by adding
the following columns:
+ "compaction_type" (text)
+ "started_at" (int)
+ "shard_id" (int)
+ "sstables_in" (list<sstableinfo_type>)
+ "sstables_out" (list<sstableinfo_type>)
+ "total_tombstone_purge_attempt" (long)
+ "total_tombstone_purge_failure_due_to_overlapping_with_memtable" (long)
+ "total_tombstone_purge_failure_due_to_overlapping_with_uncompacting_sstable" (long)
Furthermore, the commit introduces a new feature flag in order to
prevent nodes from writing data to new columns when a cluster is
not fully upgraded.
Scylla operations use concurrency semaphores to limit the number
of concurrent operations and prevent resource exhaustion. The
semaphore is selected based on the current scheduling group.
For Raft group operations, it is essential to use a system semaphore to
avoid queuing behind user operations.
This commit adds a check to ensure that the raft group0 RPCs are
executed with the `gossiper` scheduling group.
Currently if raft is enabled all nodes are voters in group0. However it is not necessary to have all nodes to be voters - it only slows down the raft group operation (since the quorum is large) and makes deployments with asymmetrical DCs problematic (2 DCs with 5 nodes along 1 DC with 10 nodes will lose the majority if large DC is isolated).
The topology coordinator will now maintain a state where there are only limited number of voters, evenly distributed across the DCs and racks.
After each node addition or removal the voters are recalculated and rebalanced if necessary. That means:
* When a new node is added, it might become a voter depending on the current distribution of voters - either if there are still some voter "slots" available, or if the new node is a better candidate than some existing voter (in which case the existing node voter status might be revoked).
* When a voter node is removed or stopped (shut down), its voter status is revoked and another node might become a voter instead (this can also depend on other circumstances, like e.g. changing the number of DCs).
* If a node addition or removal causes a change in number of data centers (DCs) or racks, the rebalance action might become wider (as there are some special rules applying to 1 vs 2 vs more DCs, also changing the number of racks might cause similar effects in the voters distribution)
Special conditions for various number of DCs:
* 1 DC: Can have up to the maximum allowed number of voters (5 - see below)
* 2 DCs: The distribution of the voters will be asymmetric (if possible), meaning that we can tolerate a loss of the DC with the smaller number of voters (if both would have the same number of voters we'd lose majority if any of the DCs is lost). For example, if we have 2 DCs with 2 nodes each, one of them will only have 1 voter (despite the limit of 5). Also, if one of the 2 DCs has more racks than the other and the node count allows it, the DC with the more racks will have more voters.
* 3 and more DCs: The distribution of the voters will be so that every DC has strictly less than half of the total voters (so a loss of any of the DCs cannot lead to the majority loss). Again, DCs with more racks are being preferred in the voter distribution.
At the moment we will be handling the zero-token nodes in the same way as the regular nodes (i.e. the zero-token nodes will not take any priority in the voter distribution). Technically it doesn't make much sense to have a zero-token node that is not a voter (when there are regular nodes in the same DC being voters), but currently the intended purpose of zero-token nodes is to form an "arbiter DC" (in case of 2 DCs, creating a third DC with zero-token nodes only), so for that intended purpose no special handling is needed and will work out of the box. If a preference of zero token nodes will eventually be needed/requested, it will be added separately from this PR.
The maximum number of voters of 5 has been chosen as the smallest "safe" value. We can lose majority when multiple nodes (possibly in different dcs and racks) die independently in a short time span. With less than 5 voters, we would lose majority if 2 voters died, which is very unlikely to happen but not entirely impossible. With 5 voters, at least 3 voters must die to lose majority, which can be safely considered impossible in the case of independent failures.
Currently the limit will not be configurable (we might introduce configurable limits later if that would be needed/requested).
Tests added:
* boost/group0_voter_registry_test.cc: run time on CI: ~3.5s
* topology_custom/test_raft_voters.py: parametrized with 1 or 3 nodes per DC, the run time on CI: 1: ~20s. 3: ~40s, approx 1 min total
Fixes: scylladb/scylladb#18793
No backport: This is a new feature that will not be backported.
Closesscylladb/scylladb#21969
* https://github.com/scylladb/scylladb:
raft: distribute voters by rack inside DC
raft/test: fix lint warnings in `test_raft_no_quorum`
raft/test: add the upgrade test for limited voters feature
raft topology: handle on_up/on_down to add/remove node from voters
raft: fix the indentation after the limited voters changes
raft: implement the limited voters feature
raft: drop the voter removal from the decommission
raft/test: disable the `stop_before_becoming_raft_voter` test
raft/test: stop the server less gracefully in the voters test
Currently if raft is enabled all nodes are voters in group0. However it
is not necessary to have all nodes to be voters - it only slows down
the raft group operation (since the quorum is large) and makes
deployments with asymmetrical DCs problematic (2 DCs with 5 nodes along
1 DC with 10 nodes will lose the majority if large DC is isolated).
The topology coordinator will now maintain a state where there are only
limited number of voters, evenly distributed across the DCs and racks.
After each node addition or removal the voters are recalculated and
rebalanced if necessary. That means:
* When a new node is added, it might become a voter depending on the
current distribution of voters - either if there are still some voter
"slots" available, or if the new node is a better candidate than some
existing voter (in which case the existing node voter status might be
revoked).
* When a voter node is removed or stopped (shut down), its voter status
is revoked and another node might become a voter instead (this can also
depend on other circumstances, like e.g. changing the number of DCs).
* If a node addition or removal causes a change in number of datacenters
(DCs) or racks, the rebalance action might become wider (as there are
some special rules applying to 1 vs 2 vs more DCs, also changing the
number of racks might cause similar effects in the voters distribution)
Special conditions for various number of DCs:
* 1 DC: Can have up to the maximum allowed number of voters (5 - see below)
* 2 DCs: The distribution of the voters will be asymmetric (if possible),
meaning that we can tolerate a loss of the DC with the smaller number
of voters (if both would have the same number of voters we'd lose the
majority if any of the DCs is lost).
For example, if we have 2 DCs with 2 nodes each, one of them will only
have 1 voter (despite the limit of 5). Also, if one of the 2 DCs has
more racks than the other and the node count allows it, the DC with
the more racks will have more voters.
* 3 and more DCs: The distribution of the voters will be so that every
DC has strictly less than half of the total voters (so a loss of any
of the DCs cannot lead to the majority loss). Again, DCs with more
racks are being preferred in the voter distribution.
At the moment we will be handling the zero-token nodes in the same way
as the regular nodes (i.e. the zero-token nodes will not take any
priority in the voter distribution). Technically it doesn't make much
sense to have a zero-token node that is not a voter (when there are
regular nodes in the same DC being voters), but currently the intended
purpose of zero-token nodes is to form an "arbiter DC" (in case of 2 DCs,
creating a third DC with zero-token nodes only), so for that intended
purpose no special handling is needed and will work out of the box.
If a preference of zero token nodes will eventually be needed/requested,
it will be added separately from this PR.
Currently the voter limits will not be configurable (we might introduce
configurable limits later if that would be needed/requested).
The feature is enabled by the `group0_limited_voters` feature flag
to avoid issues with cluster upgrade (the feature will be only enabled
once all nodes in the cluster are upgraded to the version supporting
the feature).
Fixes: scylladb/scylladb#18793
Enabled with the tablets_rack_aware_view_pairing cluster feature
rack-aware pairing pairs base to view replicas that are in the
same dc and rack, using their ordinality in the replica map
We distinguish between 2 cases:
- Simple rack-aware pairing: when the replication factor in the dc
is a multiple of the number of racks and the minimum number of nodes
per rack in the dc is greater than or equal to rf / nr_racks.
In this case (that includes the single rack case), all racks would
have the same number of replicas, so we first filter all replicas
by dc and rack, retaining their ordinality in the process, and
finally, we pair between the base replicas and view replicas,
that are in the same rack, using their original order in the
tablet-map replica set.
For example, nr_racks=2, rf=4:
base_replicas = { N00, N01, N10, N11 }
view_replicas = { N11, N12, N01, N02 }
pairing would be: { N00, N01 }, { N01, N02 }, { N10, N11 }, { N11, N12 }
Note that we don't optimize for self-pairing if it breaks pairing ordinality.
- Complex rack-aware pairing: when the replication factor is not
a multiple of nr_racks. In this case, we attempt best-match
pairing in all racks, using the minimum number of base or view replicas
in each rack (given their global ordinality), while pairing all the other
replicas, across racks, sorted by their ordinality.
For example, nr_racks=4, rf=3:
base_replicas = { N00, N10, N20 }
view_replicas = { N11, N21, N31 }
pairing would be: { N00, N31 }\*, { N10, N11 }, { N20, N21 }
\* cross-rack pair
If we'd simply stable-sort both base and view replicas by rack,
we might end up with much worse pairing across racks:
{ N00, N11 }\*, { N10, N21 }\*, { N20, N31 }\*
\* cross-rack pair
Fixesscylladb/scylladb#17147
* This is an improvement so no backport is required
Closesscylladb/scylladb#21453
* github.com:scylladb/scylladb:
network_topology_strategy_test: add tablets rack_aware_view_pairing tests
view: get_view_natural_endpoint: implement rack-aware pairing for tablets
view: get_view_natural_endpoint: handle case when there are too few view replicas
view: get_view_natural_endpoint: track replica locator::nodes
locator: topology: consult local_dc_rack if node not found by host_id
locator: node: add dc and rack getters
feature_service: add tablet_rack_aware_view_pairing feature
view: get_view_natural_endpoint: refactor predicate function
view: get_view_natural_endpoint: clarify documentation
view: mutate_MV: optimize remote_endpoints filtering check
view: mutate_MV: lookup base and view erms synchronously
view: mutate_MV: calculate keyspace-dependent flags once
File based stream is a new feature that optimizes tablet movement
significantly. It streams the entire SSTable files without deserializing
SSTable files into mutation fragments and re-serializing them back into
SSTables on receiving nodes. As a result, less data is streamed over the
network, and less CPU is consumed, especially for data models that
contain small cells.
The following patches are imported from the scylla enterprise:
*) Merge 'Introduce file stream for tablet' from Asias He
This patch uses Seastar RPC stream interface to stream sstable files on
network for tablet migration.
It streams sstables instead of mutation fragments. The file based
stream has multiple advantages over the mutation streaming.
- No serialization or deserialization for mutation fragments
- No need to read and process each mutation fragments
- On wire data is more compact and smaller
In the test below, a significant speed up is observed.
Two nodes, 1 shard per node, 1 initial_tablets:
- Start node 1
- Insert 10M rows of data with c-s
- Bootstrap node 2
Node 1 will migration data to node2 with the file stream.
Test results:
1) File stream: bytes on wire = 1132006250 bytes, bw = 836MB/s
[shard 0:stre] stream_blob - stream_sstables[eadaa8e0-a4f2-4cc6-bf10-39ad1ce106b0]
Finished sending sstable_nr=2 files_nr=18 files={} range=(-1,9223372036854775807] bytes_sent=1132006250 stream_bw=836MB/s
[shard 0:stre] storage_service - Streaming for tablet migration of a4f68900-568a-11ee-b7b9-c2b13945eed2:1 took 1.08004s seconds
2) Mutation stream: bytes on wire = 3030004736 bytes, bw = 125410.87 KiB/s = 128MB/s
[shard 0:stre] stream_session - [Stream #406dc8b0-56b5-11ee-bc2d-000bf4871058]
Streaming plan for Tablet migration-ks1-index-0 succeeded, peers={127.0.0.1}, tx=0 KiB, 0.00 KiB/s, rx=2958989 KiB, 125410.87 KiB/s
[shard 0:stre] storage_service - Streaming for tablet migration of a4f68900-568a-11ee-b7b9-c2b13945eed2:1 took 23.5992s seconds
Test Summary:
File stream v.s. Mutation stream improvements
- Stream bandwidth = 836 / 128 (MB/s) = 6.53X
- Stream time = 23.60 / 1.08 (Seconds) = 21.85X
- Stream bytes on wire = 3030004736 / 1132006250 (Bytes)= 2.67X
Closes scylladb/scylla-enterprise#3438
* github.com:scylladb/scylla-enterprise:
tests: Add file_stream_test
streaming: Implement file stream for tablet
*) streaming: Use new take_storage_snapshot interface
The new take_storage_snapshot returns a file object instead of a file
name. This allows the file stream sender to read from the file even if
the file is deleted by compaction.
Closes scylladb/scylla-enterprise#3728
*) streaming: Protect unsupported file types for file stream
Currently, we assume the file streamed over the stream_blob rpc verb is
a sstable file. This patch rejects the unsupported file types on the
receiver side. This allows us to stream more file types later using the
current file stream infrastructure without worrying about old nodes
processing the new file types in the wrong way.
- The file_ops::noop is renamed to file_ops::stream_sstables to be
explicit about the file types
- A missing test_file_stream_error_injection is added to the idl
Fixes: #3846
Tests: test_unsupported_file_ops
Closesscylladb/scylla-enterprise#3847
*) idl: Add service::session_id id to idl
It will be used in the next patch.
Refs #3907
*) streaming: Protect file stream with topology_guard
Similar to "storage_service, tablets: Use session to guard tablet
streaming", this patch protects file stream with topology_guard.
Fixes#3907
*) streaming: Take service topology_guard under the try block
Taking the service::topology_guard could throw. Currently, it throws
outside the try block, so the rpc sink will not be closed, causing the
following assertion:
```
scylla: seastar/include/seastar/rpc/rpc_impl.hh:815: virtual
seastar::rpc::sink_impl<netw::serializer,
streaming::stream_blob_cmd_data>::~sink_impl() [Serializer =
netw::serializer, Out = <streaming::stream_blob_cmd_data>]: Assertion
`this->_con->get()->sink_closed()' failed.
```
To fix, move more code including the topology_guard taking code to the
try block.
Fixes https://github.com/scylladb/scylla-enterprise/issues/4106Closesscylladb/scylla-enterprise#4110
*) Merge 'Preserve original SSTable state with file based tablet migration' from Raphael "Raph" Carvalho
We're not preserving the SSTable state across file based migration, so
staging SSTables for example are being placed into main directory, and
consequently, we're mixing staging and non-staging data, losing the
ability to continue from where the old replica left off.
It's expected that the view update backlog is transferred from old
into new replica, as migration doesn't wait for leaving replica to
complete view update work (which can take long). Elasticity is preferred.
So this fix guarantees that the state of the SSTable will be preserved
by propagating it in form of subdirectory (each subdirectory is
statically mapped with a particular state).
The staging sstables aren't being registered into view update generator
yet, as that's supposed to be fixed in OSS (more details can be found
at https://github.com/scylladb/scylladb/issues/19149).
Fixes#4265.
Closesscylladb/scylla-enterprise#4267
* github.com:scylladb/scylla-enterprise:
tablet: Preserve original SSTable state with file based tablet migration
sstables: Add get method for sstable state
*) sstable: (Re-)add shareabled_components getter
*) Merge 'File streaming sstables: Use sstable source/sink to transfer snapshots' from Calle Wilund
Fixes#4246
Alternative approach/better separation of concern, transport vs. sstable layer. Builds on #4472, but fancier.
Ensures we transfer and pre-process scylla metadata for streamed
file blobs first, then properly apply receiving nodes local config
by using a source and sink layer exported from sstables, which
handles things like ordering, metadata filtering (on source) as well
as handling metadata and proper IO paths when writing data on
receiver node (sink).
This implementation maintains the statelessness of the current
design, and the delegated sink side will re-read and re-write the
metadata for each component processed. This is a little wasteful,
but the meta is small, and it is less error prone than trying to do
caching cross-shards etc. The transport is isolated from the
knowledge.
This is an alternative/complement to #4436 and #4472, fixing the
underlying issue. Note that while the layers/API:s here allows easy
fixing of other fundamental problems in the feature (such as
destination location etc), these are not included in the PR, to keep
it as close to the current behaviour as possible.
Closesscylladb/scylla-enterprise#4646
* github.com:scylladb/scylla-enterprise:
raft_tests: Copy/add a topology test with encryption
file streaming: Use sstable source/sink to transfer snapshots
sstables: Add source and sink objects + producers for transfering a snapshot
sstable::types: Add remove accessor for extension info in metadata
*) The change for error injection in merge commit 966ea5955dd8760:
File streaming now has "stream_mutation_fragments" error injection points
so test_table_dropped_during_streaming works with file streaming.
*) doc: document file-based streaming
This commit adds a description of the file-based streaming feature to the documentation.
It will be displayed in the docs using the scylladb_include_flag directive after
https://github.com/scylladb/scylladb/pull/20182 is merged, backported to branch-6.0,
and, in turn, branch-2024.2.
Refs https://github.com/scylladb/scylla-enterprise/issues/4585
Refs https://github.com/scylladb/scylla-enterprise/issues/4254Closesscylladb/scylla-enterprise#4587
*) doc: move File-based streaming to the Tablets source file-based-streaming
This commit moves the description of file-based streaming from a common include file
to the regular doc source file where tablets are described.
Closesscylladb/scylla-enterprise#4652
*) streaming: sstable_stream_sink_impl: abort: prevent null pointer dereference
Closesscylladb/scylladb#22467
File based stream is a new feature that optimizes tablet movement
significantly. It streams the entire SSTable files without deserializing
SSTable files into mutation fragments and re-serializing them back into
SSTables on receiving nodes. As a result, less data is streamed over the
network, and less CPU is consumed, especially for data models that
contain small cells.
The following patches are imported from the scylla enterprise:
*) Merge 'Introduce file stream for tablet' from Asias He
This patch uses Seastar RPC stream interface to stream sstable files on
network for tablet migration.
It streams sstables instead of mutation fragments. The file based
stream has multiple advantages over the mutation streaming.
- No serialization or deserialization for mutation fragments
- No need to read and process each mutation fragments
- On wire data is more compact and smaller
In the test below, a significant speed up is observed.
Two nodes, 1 shard per node, 1 initial_tablets:
- Start node 1
- Insert 10M rows of data with c-s
- Bootstrap node 2
Node 1 will migration data to node2 with the file stream.
Test results:
1) File stream: bytes on wire = 1132006250 bytes, bw = 836MB/s
[shard 0:stre] stream_blob - stream_sstables[eadaa8e0-a4f2-4cc6-bf10-39ad1ce106b0]
Finished sending sstable_nr=2 files_nr=18 files={} range=(-1,9223372036854775807] bytes_sent=1132006250 stream_bw=836MB/s
[shard 0:stre] storage_service - Streaming for tablet migration of a4f68900-568a-11ee-b7b9-c2b13945eed2:1 took 1.08004s seconds
2) Mutation stream: bytes on wire = 3030004736 bytes, bw = 125410.87 KiB/s = 128MB/s
[shard 0:stre] stream_session - [Stream #406dc8b0-56b5-11ee-bc2d-000bf4871058]
Streaming plan for Tablet migration-ks1-index-0 succeeded, peers={127.0.0.1}, tx=0 KiB, 0.00 KiB/s, rx=2958989 KiB, 125410.87 KiB/s
[shard 0:stre] storage_service - Streaming for tablet migration of a4f68900-568a-11ee-b7b9-c2b13945eed2:1 took 23.5992s seconds
Test Summary:
File stream v.s. Mutation stream improvements
- Stream bandwidth = 836 / 128 (MB/s) = 6.53X
- Stream time = 23.60 / 1.08 (Seconds) = 21.85X
- Stream bytes on wire = 3030004736 / 1132006250 (Bytes)= 2.67X
Closes scylladb/scylla-enterprise#3438
* github.com:scylladb/scylla-enterprise:
tests: Add file_stream_test
streaming: Implement file stream for tablet
*) streaming: Use new take_storage_snapshot interface
The new take_storage_snapshot returns a file object instead of a file
name. This allows the file stream sender to read from the file even if
the file is deleted by compaction.
Closes scylladb/scylla-enterprise#3728
*) streaming: Protect unsupported file types for file stream
Currently, we assume the file streamed over the stream_blob rpc verb is
a sstable file. This patch rejects the unsupported file types on the
receiver side. This allows us to stream more file types later using the
current file stream infrastructure without worrying about old nodes
processing the new file types in the wrong way.
- The file_ops::noop is renamed to file_ops::stream_sstables to be
explicit about the file types
- A missing test_file_stream_error_injection is added to the idl
Fixes: #3846
Tests: test_unsupported_file_ops
Closesscylladb/scylla-enterprise#3847
*) idl: Add service::session_id id to idl
It will be used in the next patch.
Refs #3907
*) streaming: Protect file stream with topology_guard
Similar to "storage_service, tablets: Use session to guard tablet
streaming", this patch protects file stream with topology_guard.
Fixes#3907
*) streaming: Take service topology_guard under the try block
Taking the service::topology_guard could throw. Currently, it throws
outside the try block, so the rpc sink will not be closed, causing the
following assertion:
```
scylla: seastar/include/seastar/rpc/rpc_impl.hh:815: virtual
seastar::rpc::sink_impl<netw::serializer,
streaming::stream_blob_cmd_data>::~sink_impl() [Serializer =
netw::serializer, Out = <streaming::stream_blob_cmd_data>]: Assertion
`this->_con->get()->sink_closed()' failed.
```
To fix, move more code including the topology_guard taking code to the
try block.
Fixes https://github.com/scylladb/scylla-enterprise/issues/4106Closesscylladb/scylla-enterprise#4110
*) Merge 'Preserve original SSTable state with file based tablet migration' from Raphael "Raph" Carvalho
We're not preserving the SSTable state across file based migration, so
staging SSTables for example are being placed into main directory, and
consequently, we're mixing staging and non-staging data, losing the
ability to continue from where the old replica left off.
It's expected that the view update backlog is transferred from old
into new replica, as migration doesn't wait for leaving replica to
complete view update work (which can take long). Elasticity is preferred.
So this fix guarantees that the state of the SSTable will be preserved
by propagating it in form of subdirectory (each subdirectory is
statically mapped with a particular state).
The staging sstables aren't being registered into view update generator
yet, as that's supposed to be fixed in OSS (more details can be found
at https://github.com/scylladb/scylladb/issues/19149).
Fixes#4265.
Closesscylladb/scylla-enterprise#4267
* github.com:scylladb/scylla-enterprise:
tablet: Preserve original SSTable state with file based tablet migration
sstables: Add get method for sstable state
*) sstable: (Re-)add shareabled_components getter
*) Merge 'File streaming sstables: Use sstable source/sink to transfer snapshots' from Calle Wilund
Fixes#4246
Alternative approach/better separation of concern, transport vs. sstable layer. Builds on #4472, but fancier.
Ensures we transfer and pre-process scylla metadata for streamed
file blobs first, then properly apply receiving nodes local config
by using a source and sink layer exported from sstables, which
handles things like ordering, metadata filtering (on source) as well
as handling metadata and proper IO paths when writing data on
receiver node (sink).
This implementation maintains the statelessness of the current
design, and the delegated sink side will re-read and re-write the
metadata for each component processed. This is a little wasteful,
but the meta is small, and it is less error prone than trying to do
caching cross-shards etc. The transport is isolated from the
knowledge.
This is an alternative/complement to #4436 and #4472, fixing the
underlying issue. Note that while the layers/API:s here allows easy
fixing of other fundamental problems in the feature (such as
destination location etc), these are not included in the PR, to keep
it as close to the current behaviour as possible.
Closesscylladb/scylla-enterprise#4646
* github.com:scylladb/scylla-enterprise:
raft_tests: Copy/add a topology test with encryption
file streaming: Use sstable source/sink to transfer snapshots
sstables: Add source and sink objects + producers for transfering a snapshot
sstable::types: Add remove accessor for extension info in metadata
*) The change for error injection in merge commit 966ea5955dd8760:
File streaming now has "stream_mutation_fragments" error injection points
so test_table_dropped_during_streaming works with file streaming.
*) doc: document file-based streaming
This commit adds a description of the file-based streaming feature to the documentation.
It will be displayed in the docs using the scylladb_include_flag directive after
https://github.com/scylladb/scylladb/pull/20182 is merged, backported to branch-6.0,
and, in turn, branch-2024.2.
Refs https://github.com/scylladb/scylla-enterprise/issues/4585
Refs https://github.com/scylladb/scylla-enterprise/issues/4254Closesscylladb/scylla-enterprise#4587
*) doc: move File-based streaming to the Tablets source file-based-streaming
This commit moves the description of file-based streaming from a common include file
to the regular doc source file where tablets are described.
Closesscylladb/scylla-enterprise#4652
*) streaming: sstable_stream_sink_impl: abort: prevent null pointer dereference
Closesscylladb/scylladb#22034
Add resize_task_info static column to system.tablets. Set or delete
resize_task_info value when the resize_decision is changed.
Reflect the column content in tablet_map.
We still have a number of issues to be solved for views with tablets.
Until they are fixed, we should prevent users from creating them,
and use the vnode-based views instead.
This patch prepares the feature for enabling views with tablets. The
feature is disabled by default, but currently it has no effect.
After all tests are adjusted to use the feature, we should depend
on the feature for deciding whether we can create materialized views
in tablet-enabled keyspaces.
The unit tests are adjusted to enable this feature explicitly, and it's
also added to the scylla sstable tool config - this tool treats all
tables as if they were tablet-based (surprisingly, with SimpleStrategy),
so for it to work on views, the new feature must be enabled.
Refs scylladb/scylladb#21832Closesscylladb/scylladb#21833
Information about the number of shares per service level will be stored
in an additional column in the service levels table, which is managed
through group0. We will need the feature to make sure that all nodes in
the cluster know about the new column before any node starts applying
group0 commands the would touch the new column.
This feature also serves a role for the legacy service levels
implementation that uses system_distributed for storage: after all nodes
are upgraded to support workload prioritization, one of the nodes will
perform a schema change operation and will add the new column.
Adds glue which causes the contents of system.dicts to be sent
in group 0 snapshots, and causes a callback to be called when
system.dicts is updated locally. The callback is currently empty
and will be hooked up to the RPC compressor tracker in one of the
next commits.
Add migration_task_info column to system.tablets. Set migration_task_info
value on migration request if the feature is enabled in the cluster.
Reflect the column content in tablet_metadata.
Currently truncating a table works by issuing an RPC to all the nodes which call `database::truncate_table_on_all_shards()`, which makes sure that older writes are dropped.
It works with tablets, but is not safe. A concurrent replication process may bring back old data.
This change makes makes TRUNCATE TABLE a topology operation, so that it excludes with other processes in the system which could interfere with it. More specifically, it makes TRUNCATE a global topology request.
Backporting is not needed.
Fixes#16411Closesscylladb/scylladb#19789
* github.com:scylladb/scylladb:
docs: docs: topology-over-raft: Document truncate_table request
storage_proxy: fix indentation and remove empty catch/rethrow
test: add tests for truncate with tablets
storage_proxy: use new TRUNCATE for tablets
truncate: make TRUNCATE a global topology operation
storage_service: move logic of wait_for_topology_request_completion()
RPC: add truncate_with_tablets RPC with frozen_topology_guard
feature_service: added cluster feature for system.topology schema change
system.topology_requests: change schema
storage_proxy: propagate group0 client and TSM dependency
The goal of merge is to reduce the tablet count for a shrinking table. Similar to how split increases the count while the table is growing. The load balancer decision to merge is implemented today (came with infrastructure introduced for split), but it wasn't handled until now.
Initial tablet count is respected while the table is in "growing mode". For example, the table leaves it if there was a need to split above the initial tablet count. After the table leaves the mode, the average size can be trusted to determine that the table is shrinking. Merge decision is emitted if the average tablet size is 50% of the target. Hysteresis is applied to avoid oscillations between split and merges.
Similar to split, the decision to merge is recorded in tablet map's resize_type field with the string "merge". This is important in case of coordinator failover, so new coordinator continues from where the old left off.
Unlike split, the preparation phase during merge is not done by the replica (with split compactions), but rather by the coordinator by co-locating sibling tablets in the same node's shard. We can define sibling tablets as tablets that have contiguous range and will become one after merge. The concept is based on the power-of-two constraint and token contiguity. For example, in a table with 4 tablets, tablets of ids 0 and 1 are siblings, 2 and 3 are also siblings.
The algorithm for co-locating sibling tablets is very simple. The balancer is responsible for it, and it will emit migrations so that "odd" tablet will follow the "even" one. For example, tablet 1 will be migrated to where tablet 0 lives. Co-location is low in priority, it's not the end of the world to delay merge, but it's not ideal to delay e.g. decommission or even regular load balancing as that can translate into temporary unbalancing, impacting the user activities. So co-location migrations will happen when there is no more important work to do.
While regular balancing is higher in priority, it will not undo the co-location work done so far. It does that by treating co-located tablets as if they were already merged. The load inversion convergence check was adjusted so balancer understand when two tablets are being migrated instead of one, to avoid oscillations.
When balancer completes co-location work for a table undergoing merge, it will put the id of the table into the resize_plan, which is about communicating with the topology coordinator that a table is ready for it. With all sibling tablets co-located, the coordinator can resize the tablet map (reduce it by a factor of 2) and record the new map into group0. All the replicas will react to it (on token metadata update) by merging the storage (memtable(s) + sstables) of sibling tablets into one.
Fixes#18181.
system test details:
test: https://github.com/pehala/scylla-cluster-tests/blob/tablets_split_merge/tablets_split_merge_test.py
yaml file: https://github.com/pehala/scylla-cluster-tests/blob/tablets_split_merge/test-cases/features/tablets/tablets-split-merge-test.yaml
instance type: i3.8xlarge
nodes: 3
target tablet size: 0.5G (scaled down by 10, to make it easier to trigger splits and merges)
description: multiple cycles of growing and shrinking the data set in order to trigger splits and merges.
data_set_size: ~100G
initial_tablets: 64, so it grew to 128 tablets on split, and back to 64 on merge.
latency of reads and writes that happened in parallel to split and merge:
```
$ for i in scylla-bench*; do cat $i | grep "Mode\|99th:\|99\.9th:"; done
Mode: write
99.9th: 3.145727ms
99th: 1.998847ms
99.9th: 3.145727ms
99th: 2.031615ms
Mode: read
99.9th: 3.145727ms
99th: 2.031615ms
99.9th: 3.145727ms
99th: 2.031615ms
Mode: write
99.9th: 3.047423ms
99th: 1.933311ms
99.9th: 3.047423ms
99th: 1.933311ms
Mode: read
99.9th: 3.145727ms
99th: 1.900543ms
99.9th: 3.145727ms
99th: 1.900543ms
Mode: write
99.9th: 5.079039ms
99th: 3.604479ms
99.9th: 35.389439ms
99th: 25.624575ms
Mode: write
99.9th: 3.047423ms
99th: 1.998847ms
99.9th: 3.047423ms
99th: 1.998847ms
Mode: read
99.9th: 3.080191ms
99th: 2.031615ms
99.9th: 3.112959ms
99th: 2.031615ms
```
Closesscylladb/scylladb#20572
* github.com:scylladb/scylladb:
docs: Document tablet merging
tests/boost: Add test to verify correctness of balancer decisions during merge
tests/topology_experimental_raft: Add tablet merge test
service: Handle exception when retrying split
service: Co-locate sibling tablets for a table undergoing merge
gms: Add cluster feature for tablet merge
service: Make merge of resize plan commutative
replica: Implement merging of compaction groups on merge completion
replica: Handle tablet merge completion
service: Implement tablet map resize for merge
locator: Introduce merge_tablet_info()
service: Rename topology::transition_state::tablet_split_finalization
service: Respect initial_tablet_count if table is in growing mode
service: Wire migration_tablet_set into the load balancer
locator: Add tablet_map::sibling_tablets()
service: Introduce sorted_replicas_for_tablet_load()
locator/tablets: Extend tablet_replica equality comparator to three-way
service: Introduce alias to per-table candidate map type
service: Add replication constraint check variant for migration_tablet_set
service: Add convergence check variant for migration_tablet_set
service: Add migration helpers for migration_tablet_set
service/tablet_allocator: Introduce migration_tablet_set
service: Introduce migration_plan::add(migrations_vector)
locator/tablets: Introduce tablet_map::for_each_sibling_tablets()
locator/tablets: Introduce tablet_map::needs_merge()
locator/tablets: Introduce resize_decision::initial_decision()
locator/tablets: Fix return type of three-way comparison operators
service: Extract update of node load on migrations
service: Extract converge check for intra-node migration
service: Extract erase of tablet replicas from candidate list
scripts/tablet-mon: Allow visualization of tablet id
This patch adds a feature serive which protects the system.topology
schema change against situations where clusters are incompletely
upgraded to new a version and could be rolled back.
The reason we need it is that tablet merge can only be finalized
when the cluster agrees on the feature, otherwise unpatched
nodes would fail to handle merge finalization, potentially
crashing.
Signed-off-by: Raphael S. Carvalho <raphaelsc@scylladb.com>
RPCs from old nodes will still use old format so translation will be
used in this case. The change is backwards compatible thanks to RPC
extensibility.
This adds a new tablet migration kind: repair. It allows tablet repair
scheduler to use this migration kind to schedule repair jobs.
The current repair scheduler implementation does the following:
- A tablet is picked to be repaired when the time since last repair is
bigger than a threshold (auto repair mode) or it is requested by user
(manual repair mode)
- The tablet repair can be scheduled along with tablet migration and
rebuild. It runs in the tablet_migration track.
- Repair jobs are scheduled in a smart way so that at any point in time,
there are no more than configured jobs per shard, which is similar to
scylla manager's control.
In this patch, both the manual repair and the auto repair are not
enabled yet.
these unused includes are identified by clang-include-cleaner.
after auditing the source files, all of the reports have been
confirmed.
Signed-off-by: Kefu Chai <kefu.chai@scylladb.com>
Migrate the `system_distributed.view_build_status` table to `system.view_build_status_v2`. The writes to the v2 table are done via raft group0 operations.
The new parameter `view_builder_version` stored in `scylla_local` indicates whether nodes should use the old or the new table.
New clusters use v2. Otherwise, the migration to v2 is initiated by the topology coordinator when the feature is enabled. It reads all the rows from the old table and writes them to the new table, and sets `view_builder_version` to v2. When the change is applied, all view_builder services are updated to write and read from the v2 table.
The old table `system_distributed.view_build_status` is set to read virtually from the new table in order to maintain compatibility.
When removing a node from the cluster, we remove its rows from the table atomically (fixes https://github.com/scylladb/scylladb/issues/11836). Also, during the migration, we remove all invalid rows.
Fixesscylladb/scylladb#15329
dtest https://github.com/scylladb/scylla-dtest/pull/4827Closesscylladb/scylladb#19745
* github.com:scylladb/scylladb:
view: test view_build_status table with node replace
test/pylib: use view_build_status_v2 table in wait_for_view
view_builder: common write view_build_status function
view_builder: improve migration to v2 with intermediate phase
view: delete node rows from view_build_status on node removal
view: sanitize view_build_status during migration
view: make old view_build_status table a virtual table
replica: move streaming_reader_lifecycle_policy to header file
view_builder: test view_build_status_v2
storage_service: add view_build_status to raft snapshot
view_builder: migration to v2
db:system_keyspace: add view_builder_version to scylla_local
view_builder: read view status from v2 table
view_builder: introduce writing status mutations via raft
view_builder: pass group0_client and qp to view_builder
view_builder: extract sys_dist status operations to functions
db:system_keyspace: add view_build_status_v2 table
Migrate view_builder to v2, to store the view build status of all nodes
in the group0 based table view_build_status_v2.
Introduce a feature view_build_status_on_group0 so we know when all
nodes are ready to migrate and use the new table.
A new cluster is initialized to use v2. Otherwise, The topology coordinator
initiates the migration when the feature is enabled, if it was not done
already.
The migration reads all the rows in the v1 table and writes it via
group0 to the v2 table, together with a mutation that updates the
view_builder parameter in scylla_local to v2. When this mutation is
applied, it updates the view_builder service to start using the v2
table.
Hides the functionality behind a cluster feature, i.e. postspones
using it until an upgrade is complete etc. This to allow rolling back
even with dirty nodes, at least until a cluster is commited.
Feature can also be disabled by scylla option, just in case. This will
lock it out of whole cluster, but this is probably good, because depending
on off or on, certain schema/raft ops might fail or succeed (due to large
mutations), and this should probably be equivalent across nodes.
Zero-token nodes must be supported by all nodes in the cluster.
Otherwise, the non-supporting nodes would crash on some assertion
that assumes only token-owing normal nodes make sense.
Hence, we introduce the ZERO_TOKEN_NODES cluster feature. Zero-token
nodes refuse to boot if it is not supported.
I tested this patch manually. First, I booted a node built in the
previous patch. Then, I tried to add a zero-token node built in this
patch. It refused to boot as expected.
This patch adds `suppress_features` error injection. It allows to revoke
support for some features and it can be used to simulate upgrade process
in test.py.
Features to suppress are passed as injection's value, separated by `;`.
Example: `PARALLELIZED_AGGREGATION;UDA_NATIVE_PARALLELIZED_AGGREGATION`
Fixesscylladb/scylladb#20034Closesscylladb/scylladb#20055
topology_requests table will be used by task manager node ops tasks,
but it loses info about request type, which is required by tasks.
Add request_type column to topology_requests.
This feature corrected how we store the token in secondary indexes. It
was introduced in 7ff72b0ba5 (2020; 4.4) and can now be assumed present
everywhere. Note that we still support indexes created with the old format.
