In case an sstable unit test case is run individually, it would fail
with exception saying that S3_... environment is not set. It's better to
skip the test-case rather than fail. If someone wants to run it from
shell, it will have to prepare S3 server (minio/AWS public bucket) and
provide proper environment for the test-case.
refs: #13569
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
Closes#13755
Raft replication doesn't guarantee that all replicas see
identical Raft state at all times, it only guarantees the
same order of events on all replicas.
When comparing raft state with gossip state on a node, first
issue a read barrier to ensure the node has the latest raft state.
To issue a read barrier it is sufficient to alter a non-existing
state: in order to validate the DDL the node needs to sync with the
leader and fetch its latest group0 state.
Fixes#13518 (flaky topology test).
Closes#13756
Currently there are only 2 tests for S3 -- the pure client test and compound object_store test that launches scylla, creates s3-backed table and CQL-queries it. At the same time there's a whole lot of small unit test for sstables functionality, part of it can run over S3 storage too.
This PR adds this support and patches several test cases to use it. More test cases are to come later on demand.
fixes: #13015Closes#13569
* github.com:scylladb/scylladb:
test: Make resharding test run over s3 too
test: Add lambda to fetch bloom filter size
test: Tune resharding test use of sstable::test_env
test: Make datafile test case run over s3 too
test: Propagate storage options to table_for_test
test: Add support for s3 storage_options in config
test: Outline sstables::test_env::do_with_async()
test: Keep storage options on sstable_test_env config
sstables: Add and call storage::destroy()
sstables: Coroutinize sstable::destroy()
The evictable reader must ensure that each buffer fill makes forward
progress, i.e. the last fragment in the buffer has a position larger
than the last fragment from the last buffer-fill. Otherwise, the reader
could get stuck in an infinite loop between buffer fills, if the reader
is evicted in-between.
The code guranteeing this forward change has a bug: when the next
expected position is a partition-start (another partition), the code
would loop forever, effectively reading all there is from the underlying
reader.
To avoid this, add a special case to ignore the progress guarantee loop
altogether when the next expected position is a partition start. In this
case, progress is garanteed anyway, because there is exactly one
partition-start fragment in each partition.
Fixes: #13491Closes#13563
This mini-series cleans up printing of ranges in utils/to_string.hh
It generalizes the helper function to work on a std::ranges::range,
with some exceptions, and adds a helper for boost::transformed_range.
It also changes the internal interface by moving `join` the the utils namespace
and use std::string rather than seastar::sstring.
Additional unit tests were added to test/boost/json_test
Fixes#13146Closes#13159
* github.com:scylladb/scylladb:
utils: to_string: get rid of utils::join
utils: to_string: get rid of to_string(std::initializer_list)
utils: to_string: get rid of to_string(const Range&)
utils: to_string: generalize range helpers
test: add string_format_test
utils: chunked_vector: add std::ranges::range ctor
DynamoDB limits the allowed magnitude and precision of numbers - valid
decimal exponents are between -130 and 125 and up to 38 significant
decimal digitst are allowed. In contrast, Scylla uses the CQL "decimal"
type which offers unlimited precision. This can cause two problems:
1. Users might get used to this "unofficial" feature and start relying
on it, not allowing us to switch to a more efficient limited-precision
implementation later.
2. If huge exponents are allowed, e.g., 1e-1000000, summing such a
number with 1.0 will result in a huge number, huge allocations and
stalls. This is highly undesirable.
This series adds more tests in this area covering additional corner cases,
and then fixes the issue by adding the missing verification where it's
needed. After the series, all 12 tests in test/alternator/test_number.py now pass.
Fixes#6794Closes#13743
* github.com:scylladb/scylladb:
alternator: unit test for number magnitude and precision function
alternator: add validation of numbers' magnitude and precision
test/alternator: more tests for limits on number precision and magnitude
test/alternator: reproducer for DoS in unlimited-precision addition
This is a translation of Cassandra's CQL unit test source file
validation/operations/InsertUpdateIfConditionTest.java into our cql-pytest
framework.
This test file checks various LWT conditional updates which involve
collections or UDTs (there is a separate test file for LWT conditional
updates which do not involve collections, which I haven't translated
yet).
The tests reproduce one known bug:
Refs #5855: lwt: comparing NULL collection with empty value in IF
condition yields incorrect results
And also uncovered three previously-unknown bugs:
Refs #13586: Add support for CONTAINS and CONTAINS KEY in LWT expressions
Refs #13624: Add support for UDT subfields in LWT expression
Refs #13657: Misformatted printout of column name in LWT error message
Beyond those bona-fide bugs, this test also demonstrates several places
where we intentionally deviated from Cassandra's behavior, forcing me
to comment out several checks. These deviations are known, and intentional,
but some of them are undocumented and it's worth listing here the ones
re-discovered by this test:
1. On a successful conditional write, Cassandra returns just True, Scylla
also returns the old contents of the row. This difference is officially
documented in docs/kb/lwt-differences.rst.
2. Scylla allows the test "l = [null]" or "s = {null}" with this weird
null element (the result is false), whereas Cassandra prints an error.
3. Scylla allows "l[null]" or "m[null]" (resulting in null), Cassandra
prints an error.
4. Scylla allows a negative list index, "l[-2]", resulting in null.
Cassandra prints an error in this case.
5. Cassandra allows in "IF v IN (?, ?)" to bind individual values to
UNSET_VALUE and skips them, Scylla treats this as an error. Refs #13659.
6. Scylla allows "IN null" (the condition just fails), Cassandra prints
an error in this case.
Signed-off-by: Nadav Har'El <nyh@scylladb.com>
Closes#13663
Now when the test case and used lib/utils code is using storage-agnostic
approach, it can be extended to run over S3 storage as well.
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
The resharding test compares bloom filter sizes before and after reshard
runs. For that it gets the filter on-disk filename and stat()s it. That
won't work with S3 as it doesn't have its accessable on-disk files.
Some time ago there existed the storage::get_stats() method, but now
it's gone. The new s3::client::get_object_stat() is coming, but it will
take time to switch to it. For now, generalize filter size fetching into
a local lambda. Next patch will make a stub in it for S3 case, and once
the get_object_stat() is there we'll be able to smoothly start using it.
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
The test case in question spawns async context then makes the test_env
instance on the stack (and stopper for it too). There's helper for the
above steps, better to use them.
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
Most of the sstable_datafile test cases are capable of running with S3
storage, so this patch makes the simplest of them do it. Patching the
rest from this file is optional, because mostly the cases test how the
datafile data manipulations work without checking the files
manipulations. So even if making them all run over S3 is possible, it
will just increase the testing time w/o real test of the storage driver.
So this patch makes one test case run over local and S3 storages, more
patches to update more test cases with files manipulations are yet to
come.
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
Teach table_for_tests use any storage options, not just local one. For
now the only user that passes non-local options is sstables::test_env.
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
When the sstable test case wants to run over S3 storage it needs to
specify that in test config by providing the S3 storage options. So
first thing this patch adds is the helper that makes these options based
on the env left by minio launcher from test.py.
Next, in order to make sstables_manager work with S3 it needs the
plugged system keyspace which, in turn, needs query processor, proxy,
database, etc. All this stuff lives in cql_test_env, so the test case
running with S3 options will run in a sstables::test_env nested inside
cql_test_env. The latter would also need to plug its system keyspace to
the former's sstables manager and turn the experimental feature ON.
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
We have known for a long time (see issue #1703) that the quality of our
CQL "syntax error" messages leave a lot to be desired, especially when
compared to Cassandra. This patch doesn't yet bring us great error
messages with great context - doing this isn't easy and it appears that
Antlr3's C++ runtime isn't as good as the Java one in this regard -
but this patch at least fixes **garbage** printed in some error messages.
Specifically, when the parser can deduce that a specific token is missing,
it used to print
line 1:83 missing ')' at '<missing '
After this patch we get rid of the meaningless string '<missing ':
line 1:83 : Missing ')'
Also, when the parser deduced that a specific token was unneeded, it
used to print:
line 1:83 extraneous input ')' expecting <invalid>
Now we got rid of this silly "<invalid>" and write just:
line 1:83 : Unexpected ')'
Refs #1703. I didn't yet marked that issue "fixed" because I think a
complete fix would also require printing the entire misparsed line and the
point of the parse failure. Scylla still prints a generic "Syntax Error"
in most cases now, and although the character number (83 in the above
example) can help, it's much more useful to see the actual failed
statement and where character 83 is.
Unfortunately some tests enshrine buggy error messages and had to be
fixed. Other tests enshrined strange text for a generic unexplained
error message, which used to say " : syntax error..." (note the two
spaces and elipses) and after this patch is " : Syntax error". So
these tests are changed. Another message, "no viable alternative at
input" is deliberately kept unchanged by this patch so as not to break
many more tests which enshrined this message.
Signed-off-by: Nadav Har'El <nyh@scylladb.com>
Closes#13731
So that it could be set to s3 by the test case on demand. Default is
local storage which uses env's tempdir or explicit path argument.
Signed-off-by: Pavel Emelyanov <xemul@scylladb.com>
In the previous patch we added a limit in Alternator for the magnitude
and precision of numbers, based on a function get_magnitude_and_precision
whose implementation was, unfortunately, rather elaborate and delicate.
Although we did add in the previous patches some end-to-end tests which
confirmed that the final decision made based on this function, to accept or
reject numbers, was a correct decision in a few cases, such an elaborate
function deserves a separate unit test for checking just that function
in isolation. In fact, this unit tests uncovered some bugs in the first
implementation of get_magnitude_and_precision() which the other tests
missed.
Signed-off-by: Nadav Har'El <nyh@scylladb.com>
DynamoDB limits the allowed magnitude and precision of numbers - valid
decimal exponents are between -130 and 125 and up to 38 significant
decimal digitst are allowed. In contrast, Scylla uses the CQL "decimal"
type which offers unlimited precision. This can cause two problems:
1. Users might get used to this "unofficial" feature and start relying
on it, not allowing us to switch to a more efficient limited-precision
implementation later.
2. If huge exponents are allowed, e.g., 1e-1000000, summing such a
number with 1.0 will result in a huge number, huge allocations and
stalls. This is highly undesirable.
After this patch, all tests in test/alternator/test_number.py now
pass. The various failing tests which verify magnitude and precision
limitations in different places (key attributes, non-key attributes,
and arithmetic expressions) now pass - so their "xfail" tags are removed.
Fixes#6794
Signed-off-by: Nadav Har'El <nyh@scylladb.com>
We already have xfailing tests for issue #6794 - the missing checks on
precision and magnitudes of numbers in Alternator - but this patch adds
checks for additional corner cases. In particular we check the case that
numbers are used in a *key* column, which goes to a different code path
than numbers used in non-key columns, so it's worth testing as well.
Signed-off-by: Nadav Har'El <nyh@scylladb.com>
As already noted in issue #6794, whereas DynamoDB limits the magnitude
of numbers to between 10^-130 and 10^125, Scylla does not. In this patch
we add yet another test for this problem, but unlike previous tests
which just shown too much magnitude being allowed which always sounded
like a benign problem - the test in this patch shows that this "feature"
can be used to DoS Scylla - a user user can send a short request that
causes arbitrarily-large allocations, stalls and CPU usage.
The test is currently marked "skip" because it cause cause Scylla to
take a very long time and/or run out of memory. It passes on DynamoDB
because the excessive magnitude is simply not allowed there.
Refs #6794
Signed-off-by: Nadav Har'El <nyh@scylladb.com>
It's unused.
Just in case, add a unit test case for using the fmt library to
format it (that includes fmt::to_string(std::initializer_list)).
Note that the existing to_string implementation
used square brackets to enclose the initializer_list
but the new, standardized form uses curly braces.
This doesn't break anything since to_string(initializer_list)
wasn't used.
Signed-off-by: Benny Halevy <bhalevy@scylladb.com>
As seen in https://github.com/scylladb/scylladb/issues/13146
the current implementation is not general enough
to provide print helpers for all kind of containers.
Modernize the implementation using templates based
on std::ranges::range and using fmt::join.
Extend unit test for formatting different types of ranges,
boost::transformed ranges, deque.
Fixes#13146
Signed-off-by: Benny Halevy <bhalevy@scylladb.com>
In many cases we trigger offstrategy compaction opportunistically
also when there's nothing to do. In this case we still print
to the log lots of info-level message and call
`run_offstrategy_compaction` that wastes more cpu cycles
on learning that it has nothing to do.
This change bails out early if the maintenance set is empty
and prints a "Skipping off-strategy compaction" message in debug
level instead.
Fixes#13466
Also, add an group_id class and return it from compaction_group and table_state.
Use that to identify the compaction_group / table_state by "ks_name.cf_name compaction_group=idx/total" in log messages.
Fixes#13467Closes#13520
* github.com:scylladb/scylladb:
compaction_manager: print compaction_group id
compaction_group, table_state: add group_id member
compaction_manager: offstrategy compaction: skip compaction if no candidates are found
No point in going through the vector<mutation> entry-point
just to discover in run time that it was called
with a single-element vector, when we know that
in advance.
Signed-off-by: Benny Halevy <bhalevy@scylladb.com>
Closes#13733
Let's remove `expr::token` and replace all of its functionality with `expr::function_call`.
`expr::token` is a struct whose job is to represent a partition key token.
The idea is that when the user types in `token(p1, p2) < 1234`, this will be internally represented as an expression which uses `expr::token` to represent the `token(p1, p2)` part.
The situation with `expr::token` is a bit complicated.
On one hand side it's supposed to represent the partition token, but sometimes it's also assumed that it can represent a generic call to the `token()` function, for example `token(1, 2, 3)` could be a `function_call`, but it could also be `expr::token`.
The query planning code assumes that each occurence of expr::token
represents the partition token without checking the arguments.
Because of this allowing `token(1, 2, 3)` to be represented as `expr::token` is dangerous - the query planning might think that it is `token(p1, p2, p3)` and plan the query based on this, which would be wrong.
Currently `expr::token` is created only in one specific case.
When the parser detects that the user typed in a restriction which has a call to `token` on the LHS it generates `expr::token`.
In all other cases it generates an `expr::function_call`.
Even when the `function_call` represents a valid partition token, it stays a `function_call`. During preparation there is no check to see if a `function_call` to `token` could be turned into `expr::token`. This is a bit inconsistent - sometimes `token(p1, p2, p3)` is represented as `expr::token` and the query planner handles that, but sometimes it might be represented as `function_call`, which the query planner doesn't handle.
There is also a problem because there's a lot of code duplication between a `function_call` and `expr::token`.
All of the evaluation and preparation is the same for `expr::token` as it's for a `function_call` to the token function.
Currently it's impossible to evaluate `expr::token` and preparation has some flaws, but implementing it would basically consist of copy-pasting the corresponding code from token `function_call`.
One more aspect is multi-table queries.
With `expr::token` we turn a call to the `token()` function into a struct that is schema-specific.
What happens when a single expression is used to make queries to multiple tables? The schema is different, so something that is represented as `expr::token` for one schema would be represented as `function_call` in the context of a different schema.
Translating expressions to different tables would require careful manipulation to convert `expr::token` to `function_call` and vice versa. This could cause trouble for index queries.
Overall I think it would be best to remove `expr::token`.
Although having a clear marker for the partition token is sometimes nice for query planning, in my opinion the pros are outweighted by the cons.
I'm a big fan of having a single way to represent things, having two separate representations of the same thing without clear boundaries between them causes trouble.
Instead of having both `expr::token` and `function_call` we can just have the `function_call` and check if it represents a partition token when needed.
Refs: #12906
Refs: #12677Closes: #12905Closes#13480
* github.com:scylladb/scylladb:
cql3: remove expr::token
cql3: keep a schema in visitor for extract_clustering_prefix_restrictions
cql3: keep a schema inside the visitor for extract_partition_range
cql3/prepare_expr: make get_lhs_receiver handle any function_call
cql3/expr: properly print token function_call
expr_test: use unresolved_identifier when creating token
cql3/expr: split possible_lhs_values into column and token variants
cql3/expr: fix error message in possible_lhs_values
cql3: expr: reimplement is_satisfied_by() in terms of evaluate()
cql3/expr: add a schema argument to expr::replace_token
cql3/expr: add a comment for expr::has_partition_token
cql3/expr: add a schema argument to expr::has_token
cql3: use statement_restrictions::has_token_restrictions() wherever possible
cql3/expr: add expr::is_partition_token_for_schema
cql3/expr: add expr::is_token_function
cql3/expr: implement preparing function_call without a receiver
cql3/functions: make column family argument optional in functions::get
cql3/expr: make it possible to prepare expr::constant
cql3/expr: implement test_assignment for column_value
cql3/expr: implement test_assignment for expr::constant
Let's remove expr::token and replace all of its functionality with expr::function_call.
expr::token is a struct whose job is to represent a partition key token.
The idea is that when the user types in `token(p1, p2) < 1234`,
this will be internally represented as an expression which uses
expr::token to represent the `token(p1, p2)` part.
The situation with expr::token is a bit complicated.
On one hand side it's supposed to represent the partition token,
but sometimes it's also assumed that it can represent a generic
call to the token() function, for example `token(1, 2, 3)` could
be a function_call, but it could also be expr::token.
The query planning code assumes that each occurence of expr::token
represents the partition token without checking the arguments.
Because of this allowing `token(1, 2, 3)` to be represented
as expr::token is dangerous - the query planning
might think that it is `token(p1, p2, p3)` and plan the query
based on this, which would be wrong.
Currently expr::token is created only in one specific case.
When the parser detects that the user typed in a restriction
which has a call to `token` on the LHS it generates expr::token.
In all other cases it generates an `expr::function_call`.
Even when the `function_call` represents a valid partition token,
it stays a `function_call`. During preparation there is no check
to see if a `function_call` to `token` could be turned into `expr::token`.
This is a bit inconsistent - sometimes `token(p1, p2, p3)` is represented
as `expr::token` and the query planner handles that, but sometimes it might
be represented as `function_call`, which the query planner doesn't handle.
There is also a problem because there's a lot of duplication
between a `function_call` and `expr::token`. All of the evaluation
and preparation is the same for `expr::token` as it's for a `function_call`
to the token function. Currently it's impossible to evaluate `expr::token`
and preparation has some flaws, but implementing it would basically
consist of copy-pasting the corresponding code from token `function_call`.
One more aspect is multi-table queries. With `expr::token` we turn
a call to the `token()` function into a struct that is schema-specific.
What happens when a single expression is used to make queries to multiple
tables? The schema is different, so something that is representad
as `expr::token` for one schema would be represented as `function_call`
in the context of a different schema.
Translating expressions to different tables would require careful
manipulation to convert `expr::token` to `function_call` and vice versa.
This could cause trouble for index queries.
Overall I think it would be best to remove expr::token.
Although having a clear marker for the partition token
is sometimes nice for query planning, in my opinion
the pros are outweighted by the cons.
I'm a big fan of having a single way to represent things,
having two separate representations of the same thing
without clear boundaries between them causes trouble.
Instead of having expr::token and function_call we can
just have the function_call and check if it represents
a partition token when needed.
Signed-off-by: Jan Ciolek <jan.ciolek@scylladb.com>
One test for expr::token uses raw column identifier
in the test.
Let's change it to unresloved_identifier, which is
a standard representation of unresolved column
names in expressions.
Once expr::token is removed it will be possible
to create a function_call with unresolved_identifiers
as arguments.
Signed-off-by: Jan Ciolek <jan.ciolek@scylladb.com>
Add a function to check whether the expression
represents a partition token - that is a call
to the token function with consecutive partition
key columns as the arguments.
For example for `token(p1, p2, p3)` this function
would return `true`, but for `token(1, 2, 3)` or `token(p3, p2, p1)`
the result would be `false`.
The function has a schema argument because a schema is required
to get the list of partition columns that should be passed as
arguments to token().
Maybe it would be possible to infer the schema from the information
given earlier during prepare_expression, but it would be complicated
and a bit dangerous to do this. Sometimes we operate on multiple tables
and the schema is needed to differentiate between them - a token() call
can represent the base table's partition token, but for an index table
this is just a normal function call, not the partition token.
Signed-off-by: Jan Ciolek <jan.ciolek@scylladb.com>
Add a function that can be used to check
whether a given expression represents a call
to the token() function.
Note that a call to token() doesn't mean
that the expression represents a partition
token - it could be something like token(1, 2, 3),
just a normal function_call.
The code for checking has been taken from functions::get.
Signed-off-by: Jan Ciolek <jan.ciolek@scylladb.com>
Currently trying to do prepare_expression(function_call)
with a nullptr receiver fails.
It should be possible to prepare function calls without
a known receiver.
When the user types in: `token(1, 2, 3)`
the code should be able to figure out that
they are looking for a function with name `token`,
which takes 3 integers as arguments.
In order to support that we need to prepare
all arguments that can be prepared before
attempting to find a function.
Prepared expressions have a known type,
which helps to find the right function
for the given arguments.
Additionally the current code for finding
a function requires all arguments to be
assignment_testable, which requires to prepare
some expression types, e.g column_values.
Signed-off-by: Jan Ciolek <jan.ciolek@scylladb.com>
S3 wasn't providing filter size and accurate size for all SSTable components on disk.
First, filter size is provided by taking advantage that its in-memory representation is roughly the same as on-disk one.
Second, size for all components is provided by piggybacking on sstable parser and writer, so no longer a need to do a separate additional step after Scylla have either parsed or written all components.
Finally, sstable::storage::get_stats() is killed, so the burden is no longer pushed on the storage type implementation.
Refs #13649.
Closes#13682
* github.com:scylladb/scylladb:
test: Verify correctness of sstable::bytes_on_disk()
sstable: Piggyback on sstable parser and writer to provide bytes_on_disk
sstable: restore indentation in read_digest() and read_checksum()
sstable: make all parsing of simple components go through do_read_simple()
sstable: Add missing pragma once to random_access_reader.hh
sstable: make all writing of simple components go through do_write_simple()
test: sstable_utils: reuse set_values()
sstable: Restore indentation in read_simple()
sstable: Coroutinize read_simple()
sstable: Use filter memory footprint in filter_size()
try_prepare_expression(constant) used to throw an error
when trying to prepeare expr::constant.
It would be useful to be able to do this
and it's not hard to implement.
Signed-off-by: Jan Ciolek <jan.ciolek@scylladb.com>
the removed CMake script was designed to cater the needs when
Seastar's CMake script is not included in the parent project, but
this part is never tested and is dysfunctional as the `target_source()`
misses the target parameter. we can add it back when it is actually needed.
Signed-off-by: Kefu Chai <kefu.chai@scylladb.com>
bytes_on_disk is the sum of all sstable components.
As read_simple() fetches the file size before parsing the component,
bytes_on_disk can be added incrementally rather than an additional
step after all components were already parsed.
Likewise, write_simple() tracks the offset for each new component,
and therefore bytes_on_disk can also be added incrementally.
This simplifies s3 life as it no longer have to care about feeding
a bytes_on_disk, which is currently limited to data and index
sizes only.
Refs #13649.
Signed-off-by: Raphael S. Carvalho <raphaelsc@scylladb.com>
This PR introduces an experimental feature called "tablets". Tablets are
a way to distribute data in the cluster, which is an alternative to the
current vnode-based replication. Vnode-based replication strategy tries
to evenly distribute the global token space shared by all tables among
nodes and shards. With tablets, the aim is to start from a different
side. Divide resources of replica-shard into tablets, with a goal of
having a fixed target tablet size, and then assign those tablets to
serve fragments of tables (also called tablets). This will allow us to
balance the load in a more flexible manner, by moving individual tablets
around. Also, unlike with vnode ranges, tablet replicas live on a
particular shard on a given node, which will allow us to bind raft
groups to tablets. Those goals are not yet achieved with this PR, but it
lays the ground for this.
Things achieved in this PR:
- You can start a cluster and create a keyspace whose tables will use
tablet-based replication. This is done by setting `initial_tablets`
option:
```
CREATE KEYSPACE test WITH replication = {'class': 'NetworkTopologyStrategy',
'replication_factor': 3,
'initial_tablets': 8};
```
All tables created in such a keyspace will be tablet-based.
Tablet-based replication is a trait, not a separate replication
strategy. Tablets don't change the spirit of replication strategy, it
just alters the way in which data ownership is managed. In theory, we
could use it for other strategies as well like
EverywhereReplicationStrategy. Currently, only NetworkTopologyStrategy
is augmented to support tablets.
- You can create and drop tablet-based tables (no DDL language changes)
- DML / DQL work with tablet-based tables
Replicas for tablet-based tables are chosen from tablet metadata
instead of token metadata
Things which are not yet implemented:
- handling of views, indexes, CDC created on tablet-based tables
- sharding is done using the old method, it ignores the shard allocated in tablet metadata
- node operations (topology changes, repair, rebuild) are not handling tablet-based tables
- not integrated with compaction groups
- tablet allocator piggy-backs on tokens to choose replicas.
Eventually we want to allocate based on current load, not statically
Closes#13387
* github.com:scylladb/scylladb:
test: topology: Introduce test_tablets.py
raft: Introduce 'raft_server_force_snapshot' error injection
locator: network_topology_strategy: Support tablet replication
service: Introduce tablet_allocator
locator: Introduce tablet_aware_replication_strategy
locator: Extract maybe_remove_node_being_replaced()
dht: token_metadata: Introduce get_my_id()
migration_manager: Send tablet metadata as part of schema pull
storage_service: Load tablet metadata when reloading topology state
storage_service: Load tablet metadata on boot and from group0 changes
db, migration_manager: Notify about tablet metadata changes via migration_listener::on_update_tablet_metadata()
migration_notifier: Introduce before_drop_keyspace()
migration_manager: Make prepare_keyspace_drop_announcement() return a future<>
test: perf: Introduce perf-tablets
test: Introduce tablets_test
test: lib: Do not override table id in create_table()
utils, tablets: Introduce external_memory_usage()
db: tablets: Add printers
db: tablets: Add persistence layer
dht: Use last_token_of_compaction_group() in split_token_range_msb()
locator: Introduce tablet_metadata
dht: Introduce first_token()
dht: Introduce next_token()
storage_proxy: Improve trace-level logging
locator: token_metadata: Fix confusing comment on ring_range()
dht, storage_proxy: Abstract token space splitting
Revert "query_ranges_to_vnodes_generator: fix for exclusive boundaries"
db: Exclude keyspace with per-table replication in get_non_local_strategy_keyspaces_erms()
db: Introduce get_non_local_vnode_based_strategy_keyspaces()
service: storage_proxy: Avoid copying keyspace name in write handler
locator: Introduce per-table replication strategy
treewide: Use replication_strategy_ptr as a shorter name for abstract_replication_strategy::ptr_type
locator: Introduce effective_replication_map
locator: Rename effective_replication_map to vnode_effective_replication_map
locator: effective_replication_map: Abstract get_pending_endpoints()
db: Propagate feature_service to abstract_replication_strategy::validate_options()
db: config: Introduce experimental "TABLETS" feature
db: Log replication strategy for debugging purposes
db: Log full exception on error in do_parse_schema_tables()
db: keyspace: Remove non-const replication strategy getter
config: Reformat
in C++20, compiler generate operator!=() if the corresponding
operator==() is already defined, the language now understands
that the comparison is symmetric in the new standard.
fortunately, our operator!=() is always equivalent to
`! operator==()`, this matches the behavior of the default
generated operator!=(). so, in this change, all `operator!=`
are removed.
in addition to the defaulted operator!=, C++20 also brings to us
the defaulted operator==() -- it is able to generated the
operator==() if the member-wise lexicographical comparison.
under some circumstances, this is exactly what we need. so,
in this change, if the operator==() is also implemented as
a lexicographical comparison of all memeber variables of the
class/struct in question, it is implemented using the default
generated one by removing its body and mark the function as
`default`. moreover, if the class happen to have other comparison
operators which are implemented using lexicographical comparison,
the default generated `operator<=>` is used in place of
the defaulted `operator==`.
sometimes, we fail to mark the operator== with the `const`
specifier, in this change, to fulfil the need of C++ standard,
and to be more correct, the `const` specifier is added.
also, to generate the defaulted operator==, the operand should
be `const class_name&`, but it is not always the case, in the
class of `version`, we use `version` as the parameter type, to
fulfill the need of the C++ standard, the parameter type is
changed to `const version&` instead. this does not change
the semantic of the comparison operator. and is a more idiomatic
way to pass non-trivial struct as function parameters.
please note, because in C++20, both operator= and operator<=> are
symmetric, some of the operators in `multiprecision` are removed.
they are the symmetric form of the another variant. if they were
not removed, compiler would, for instance, find ambiguous
overloaded operator '=='.
this change is a cleanup to modernize the code base with C++20
features.
Signed-off-by: Kefu Chai <kefu.chai@scylladb.com>
Closes#13687
Common compression libraries work on contiguous buffers.
Contiguous buffers are a problem for the allocator. However, as long as they are short-lived,
we can avoid the expensive allocations by reusing buffers across tasks.
This idea is already applied to the compression of CQL frames, but with some deficiencies.
`utils: redesign reusable_buffer` attempts to improve upon it in a few ways. See its commit message for an extended discussion.
Compression buffer reuse also happens in the zstd SSTable compressor, but the implementation is misguided. Every `zstd_processor` instance reuses a buffer, but each instance has its own buffer. This is very bad, because a healthy database might have thousands of concurrent instances (because there is one for each sstable reader). Together, the buffers might require gigabytes of memory, and the reuse actually *increases* memory pressure significantly, instead of reducing it.
`zstd: share buffers between compressor instances` aims to improve that by letting a single buffer be shared across all instances on a shard.
Closes#13324
* github.com:scylladb/scylladb:
zstd: share buffers between compressor instances
utils: redesign reusable_buffer
Large contiguous buffers put large pressure on the allocator
and are a common source of reactor stalls. Therefore, Scylla avoids
their use, replacing it with fragmented buffers whenever possible.
However, the use of large contiguous buffers is impossible to avoid
when dealing with some external libraries (i.e. some compression
libraries, like LZ4).
Fortunately, calls to external libraries are synchronous, so we can
minimize the allocator impact by reusing a single buffer between calls.
An implementation of such a reusable buffer has two conflicting goals:
to allocate as rarely as possible, and to waste as little memory as
possible. The bigger the buffer, the more likely that it will be able
to handle future requests without reallocation, but also the memory
memory it ties up.
If request sizes are repetitive, the near-optimal solution is to
simply resize the buffer up to match the biggest seen request,
and never resize down.
However, if we anticipate pathologically large requests, which are
caused by an application/configuration bug and are never repeated
again after they are fixed, we might want to resize down after such
pathological requests stop, so that the memory they took isn't tied
up forever.
The current implementation of reusable buffers handles this by
resizing down to 0 every 100'000 requests.
This patch attempts to solve a few shortcomings of the current
implementation.
1. Resizing to 0 is too aggressive. During regular operation, we will
surely need to resize it back to the previous size again. If something
is allocated in the hole left by the old buffer, this might cause
a stall. We prefer to resize down only after pathological requests.
2. When resizing, the current implementation allocates the new buffer
before freeing the old one. This increases allocator pressure for no
reason.
3. When resizing up, the buffer is resized to exactly the requested
size. That is, if the current size is 1MiB, following requests
of 1MiB+1B and 1MiB+2B will both cause a resize.
It's preferable to limit the set of possible sizes so that every
reset doesn't tend to cause multiple resizes of almost the same size.
The natural set of sizes is powers of 2, because that's what the
underlying buddy allocator uses. No waste is caused by rounding up
the allocation to a power of 2.
4. The interval of 100'000 uses is both too low and too arbitrary.
This is up for discussion, but I think that it's preferable to base
the dynamics of the buffer on time, rather than the number of uses.
It's more predictable to humans.
The implementation proposed in this patch addresses these as follows:
1. Instead of resizing down to 0, we resize to the biggest size
seen in the last period.
As long as at least one maximal (up to a power of 2) "normal" request
appears each period, the buffer will never have to be resized.
2. The capacity of the buffer is always rounded up to the nearest
power of 2.
3. The resize down period is no longer measured in number of requests
but in real time.
Additionally, since a shared buffer in asynchronous code is quite a
footgun, some rudimentary refcounting is added to assert that only
one reference to the buffer exists at a time, and that the buffer isn't
downsized while a reference to it exists.
Fixes#13437
std::rel_ops was deprecated in C++20, as C++20 provides a better solution for defining comparison operators. and all the use cases previously to be addressed by `using namespace std::rel_ops` have been addressed either by `operator<=>` or the default-generated `operator!=`.
so, in this series, to avoid using deprecated facilities, let's drop all these `using namespace std::rel_ops`. there are many more cases where we could either use `operator<=>` or the default-generated `operator!=` to simplify the implementation. but here, we care more about `std::rel_ops`, we will drop the most (if not all of them) of the explicitly defined `operator!=` and other comparison operators later.
Closes#13676
* github.com:scylladb/scylladb:
treewide: do not use std::rel_ops
dht: token: s/tri_compare/operator<=>/
Fix two issues with the replace operation introduced by recent PRs.
Add a test which performs a sequence of basic topology operations (bootstrap,
decommission, removenode, replace) in a new suite that enables the `raft`
experimental feature (so that the new topology change coordinator code is used).
Fixes: #13651Closes#13655
* github.com:scylladb/scylladb:
test: new suite for testing raft-based topology
test: remove topology_custom/test_custom.py
raft topology: don't require new CDC generation UUID to always be present
raft topology: include shard_count/ignore_msb during replace
std::rel_ops was deprecated in C++20, as C++20 provides a better
solution for defining comparison operators. and all the use cases
previously to be addressed by `using namespace std::rel_ops` have
been addressed either by `operator<=>` or the default-generated
`operator!=`.
so, in this change, to avoid using deprecated facilities, let's
drop all these `using namespace std::rel_ops`.
Signed-off-by: Kefu Chai <kefu.chai@scylladb.com>
this is a part of a series to migrating from `operator<<(ostream&, ..)`
based formatting to fmtlib based formatting. the goal here is to enable
fmtlib to print `range_tombstone_list` and `range_tombstone_entry`
without the help of `operator<<`.
the corresponding `operator<<()` for `range_tombstone_entry` is moved
into test, where it is used. and the other one is dropped in this change,
as all its callers are now using fmtlib for formatting now.
Refs #13245
Signed-off-by: Kefu Chai <kefu.chai@scylladb.com>
Closes#13627
Fix a few cases where instead of printing column names in error messages, we printed weird stuff like ASCII codes or the address of the name.
Fixes#13657Closes#13658
* github.com:scylladb/scylladb:
cql3: fix printing of column_specification::name in some error messages
cql3: fix printing of column_definition::name in some error messages
