Instead of lengthy blurbs, switch to single-line, machine-readable
standardized (https://spdx.dev) license identifiers. The Linux kernel
switched long ago, so there is strong precedent.
Three cases are handled: AGPL-only, Apache-only, and dual licensed.
For the latter case, I chose (AGPL-3.0-or-later and Apache-2.0),
reasoning that our changes are extensive enough to apply our license.
The changes we applied mechanically with a script, except to
licenses/README.md.
Closes#9937
We want to rewrite the above mentioned method's implementation in terms
of the standard query result building code (that of the `data_query()`
path), in order to retire the alternative query code in the mutation
class.
The `data_query()` code uses classes private to `mutation_partition.cc`
and instead of making these public, just move `to_data_query_result()`
to `mutation_partition.cc`.
Currently, we cannot select more than 2^32 rows from a table because we are limited by types of
variables containing the numbers of rows. This patch changes these types and sets new limits.
The new limits take effect while selecting all rows from a table - custom limits of rows in a result
stay the same (2^32-1).
In classes which are being serialized and used in messaging, in order to be able to process queries
originating from older nodes, the top 32 bits of new integers are optional and stay at the end
of the class - if they're absent we assume they equal 0.
The backward compatibility was tested by querying an older node for a paged selection, using the
received paging_state with the same select statement on an upgraded node, and comparing the returned
rows with the result generated for the same query by the older node, additionally checking if the
paging_state returned by the upgraded node contained new fields with correct values. Also verified
if the older node simply ignores the top 32 bits of the remaining rows number when handling a query
with a paging_state originating from an upgraded node by generating and sending such a query to
an older node and checking the paging_state in the reply(using python driver).
Fixes#5101.
If somebody wants to bypass proper memory accounting they should at
the very least be forced to consider if that is indeed wise and think a
second about the limit they want to apply.
Usually, a reconcilable_result holds very few partitions (1 is common),
since the page size is limited by 1MB. But if we have paging disabled or
if we are reconciling a range full of tombstones, we may see many more.
This can cause large allocations.
Change to chunked_vector to prevent those large allocations, as they
can be quite expensive.
Fixes#4780.
Introduce class result_options to carry result options through the
request pipeline, which at this point mean the result type and the
digest algorithm. This class allows us to encapsulate the concrete
digest algorithm to use.
Signed-off-by: Duarte Nunes <duarte@scylladb.com>
This patch changes mutation_query::to_data_query_result() so that it
enforces the row limit alongside the partition limit and the
per-partition limit.
In the following patch, we'll enforce the row limit in an upper layer,
but this lets us optimize the case where only when replica replies.
Signed-off-by: Duarte Nunes <duarte@scylladb.com>
reconcilable_result can be merged with another or transformed into
query::result. Make sure that short_read information is never lost.
Signed-off-by: Paweł Dziepak <pdziepak@scylladb.com>
"Currently data query digest includes cells and tombstones which may have
expired or be covered by higher-level tombstones. This causes digest
mismatch between replicas if some elements are compacted on one of the
nodes and not on others. This mismatch triggers read-repair which doesn't
resolve because mutations received by mutation queries are not differing,
they are compacted already.
The fix adds compacting step before writing and digesting query results by
reusing the algorithm used by mutation query. This is not the most optimal
way to fix this. The compaction step could be folded with the query writing,
there is redundancy in both steps. However such change carries more risk,
and thus was postponed.
perf_simple_query test (cassandra-stress-like partitions) shows regression
from 83k to 77k (7%) ops/s.
Fixes #1165."
Currently data query digest includes cells and tombstones which may have
expired or be covered by higher-level tombstones. This causes digest
mismatch between replicas if some elements are compacted on one of the
nodes and not on others. This mismatch triggers read-repair which doesn't
resolve because mutations received by mutation queries are not differing,
they are compacted already.
The fix adds compacting step before writing and digesting query results by
reusing the algorithm used by mutation query. This is not the most optimal
way to fix this. The compaction step could be folded with the query writing,
there is redundancy in both steps. However such change carries more risk,
and thus was postponed.
perf_simple_query test (cassandra-stress-like partitions) shows regression
from 83k to 77k (7%) ops/s.
Fixes#1165.
The query result footprint for cassandra-stress mutation as reported
by tests/memory-footprint increased by 18% from 285 B to 337 B.
perf_simple_query shows slight regression in throughput (-8%):
build/release/tests/perf/perf_simple_query -c4 -m1G --partitions 100000
Before: ~433k tps
After: ~400k tps
We call a mutation source during the query path without any consideration
for attaching a priority. This is incorrect, and queries called through this
facility will end up in the default class.
Fix this by attaching the query priority class here.
Signed-off-by: Glauber Costa <glauber@scylladb.com>
In same cases we may have a lot of empty partitions whose tombstones
expired, and there is no point in including them in the results.
This was found to cause performance issues for workloads using batch
updates. system.batchlog table would accumulate a lot of deletes over
time. It has gc_grace_seconds set to 0 so most of the tombstones would
be expired. mutation queries done by batchlog manager were still
returning all partitions present in memtables which caused mutation
queries result to be inflated. This in turn was causing
mutation_result_merger to take a long time to process them.
The intent is to make data returned by queries always conform to a
single schema version, which is requested by the client. For CQL
queries, for example, we want to use the same schema which was used to
compile the query. The other node expects to receive data conforming
to the requested schema.
Interface on shard level accepts schema_ptr, across nodes we use
table_schema_version UUID. To transfer schema_ptr across shards, we
use global_schema_ptr.
Because schema is identified with UUID across nodes, requestors must
be prepared for being queried for the definition of the schema. They
must hold a live schema_ptr around the request. This guarantees that
schema_registry will always know about the requested version. This is
not an issue because for queries the requestor needs to hold on to the
schema anyway to be able to interpret the results. But care must be
taken to always use the same schema version for making the request and
parsing the results.
Schema requesting across nodes is currently stubbed (throws runtime
exception).
Allows for having more than one clustering row range set, depending on
PK queried (although right now limited to one - which happens to be exactly
the number of mutiplexing paging needs... What a coincidence...)
Encapsulates the row_ranges member in a query function, and if needed holds
ranges outside the default one in an extra object.
Query result::builder::add_partition now fetches the correct row range for
the partition, and this is the range used in subsequent iteration.
In case of SELECT DISTINCT statments we are not intersted in clustering
keys at all. The only important information is whether partition key
exists and what's in static row (if it exists).
Signed-off-by: Paweł Dziepak <pdziepak@cloudius-systems.com>
Mutation query differs from data query in that returns information
needed to reconcile data slice with that retruned by other data
sources.
There is a generic mutation_query() algorithm introduced, which can
work with any mutation_source.
database::query_mutations() is a shard-local interface for mutation
queries.
The reconcilable_result is introduced as a medium for mutation query
results. It piggy backs on frozen_mutation as a medium for
reconcilable data.
