It semms that GEQO optimizations, when it is set to on, create their own memory context
and free it after when it is no longer necessary. In join multi_join_restriction_hook
we allocate our variables in the CurrentMemoryContext, which is GEQO's memory context
if it is active. To prevent deallocation of our variables when GEQO's memory context is
freed, we started to allocate memory fo these variables in separate MemoryContext.
So far citus used postgres' predicate proofing logic for shard
pruning, except for INSERT and COPY which were already optimized for
speed. That turns out to be too slow:
* Shard pruning for SELECTs is currently O(#shards), because
PruneShardList calls predicate_refuted_by() for every
shard. Obviously using an O(N) type algorithm for general pruning
isn't good.
* predicate_refuted_by() is quite expensive on its own right. That's
primarily because it's optimized for doing a single refutation
proof, rather than performing the same proof over and over.
* predicate_refuted_by() does not keep persistent state (see 2.) for
function calls, which means that a lot of syscache lookups will be
performed. That's particularly bad if the partitioning key is a
composite key, because without a persistent FunctionCallInfo
record_cmp() has to repeatedly look-up the type definition of the
composite key. That's quite expensive.
Thus replace this with custom-code that works in two phases:
1) Search restrictions for constraints that can be pruned upon
2) Use those restrictions to search for matching shards in the most
efficient manner available:
a) Binary search / Hash Lookup in case of hash partitioned tables
b) Binary search for equal clauses in case of range or append
tables without overlapping shards.
c) Binary search for inequality clauses, searching for both lower
and upper boundaries, again in case of range or append
tables without overlapping shards.
d) exhaustive search testing each ShardInterval
My measurements suggest that we are considerably, often orders of
magnitude, faster than the previous solution, even if we have to fall
back to exhaustive pruning.
This determines whether it's possible to perform binary search on
sortedShardIntervalArray or not. If e.g. two shards have overlapping
ranges, that'd be prohibitive.
That'll be useful in later commit introducing faster shard pruning.
That's useful when comparing values a hash-partitioned table is
filtered by. The existing shardIntervalCompareFunction is about
comparing hashed values, not unhashed ones.
The added btree opclass function is so we can get a comparator
back. This should be changed much more widely, but is not necessary so
far.
Previously we, unnecessarily, used a the first shard's type
information to to look up the comparison function. But that
information is already available, so use it. That's helpful because
we sometimes want to access the comparator function even if there's no
shards.
With this commit, we started to send explain queries within a savepoint. After
running explain query, we rollback to savepoint. This saves us from side effects
of EXPLAIN ANALYZE on DML queries.
All callers fetch a cache entry and extract/compute arguments for the
eventual FindShardInterval call, so it makes more sense to refactor
into that function itself; this solves the use-after-free bug, too.
Soon shard pruning will be optimized not to generally work linearly
anymore. Thus we can't print the pruned shard intervals as currently
done anymore.
The current printing of shard ids also prevents us from running tests
in parallel, as otherwise shard ids aren't linearly numbered.
Pretty straightforward. Had some concerns about locking, but due to the
fact that all distributed operations use either some level of deparsing
or need to enumerate column names, they all block during any concurrent
column renames (due to the AccessExclusive lock).
In addition, I had some misgivings about permitting renames of the dis-
tribution column, but nothing bad comes from just allowing them.
Finally, I tried to trigger any sort of error using prepared statements
and could not trigger any errors not also exhibited by plain PostgreSQL
tables.
With this change, we set to default value of isactive column to true so that
upgrading users all nodes will be marked as active to not break their environment.
With this change we add an option to add a node without replicating all reference
tables to that node. If a node is added with this option, we mark the node as
inactive and no queries will sent to that node.
We also added two new UDFs;
- master_activate_node(host, port):
- marks node as active and replicates all reference tables to that node
- master_add_inactive_node(host, port):
- only adds node to pg_dist_node
Before this commit, we were erroring out for queries containing parameterized SQL functions
like 'SELECT parameterized_sql_query(value)' as we should, however we were returning wrong
results for queries like 'SELECT * FROM parameterized_sql_query(value)'. With this commit
we started to error out on such queries too.
In this PR, we aim to deduce whether each of the RTE_RELATION
is joined with at least on another RTE_RELATION on their partition keys. If each
RTE_RELATION follows the above rule, we can conclude that all RTE_RELATIONs are
joined on their partition keys.
In order to do that, we invented a new equivalence class namely:
AttributeEquivalenceClass. In very simple words, a AttributeEquivalenceClass is
identified by an unique id and consists of a list of AttributeEquivalenceMembers.
Each AttributeEquivalenceMember is designed to identify attributes uniquely within the
whole query. The necessity of this arise since varno attributes are defined within
a single level of a query. Instead, here we want to identify each RTE_RELATION uniquely
and try to find equality among each RTE_RELATION's partition key.
Whenever we find an equality clause A = B, where both A and B originates from
relation attributes (i.e., not random expressions), we create an
AttributeEquivalenceClass to record this knowledge. If we later find another
equivalence B = C, we create another AttributeEquivalenceClass. Finally, we can
apply transitity rules and generate a new AttributeEquivalenceClass which includes
A, B and C.
Note that equality among the members are identified by the varattno and rteIdentity.
Each equality among RTE_RELATION is saved using an AttributeEquivalenceClass where
each member attribute is identified by a AttributeEquivalenceMember. In the final
step, we try generate a common attribute equivalence class that holds as much as
AttributeEquivalenceMembers whose attributes are a partition keys.
This was getting pretty long and complex in the context of the main
utility hook. Moved out the checks for what should skip Citus process-
ing and what should have version checks performed.
The use of a bare src/ rather than $srcdir caused configure to fail
during VPATH builds. With our additional dependency upon AWK, we need
to call AC_PROG_AWK, otherwise environments may not have $AWK set.
Finally, citus_version.h should be in .gitignore.
With this change, we start to error out if loaded citus binaries does not match
the available major version or installed citus extension version. In this case
we force user to restart the server or run ALTER EXTENSION depending on the
situation
Thought this looked slightly nicer than the default behavior.
Changed preventTransaction to concurrent to be clearer that this code
path presently affects CONCURRENTLY code only.
Marco Slot
Burak Yucesoy
Andres Freund
Metin Doslu
Jason Petersen
Eren Basak
velioglu
Onder Kalaci