LoadShardList is called twice, which is not neccessary, and there is no
need to sort the shard placement list since we only want to know the list
length.
This change adds a script to programatically group all includes in a
specific order. The script was used as a one time invocation to group
and sort all includes throught our formatted code. The grouping is as
follows:
- System includes (eg. `#include<...>`)
- Postgres.h (eg. `#include "postgres.h"`)
- Toplevel imports from postgres, not contained in a directory (eg.
`#include "miscadmin.h"`)
- General postgres includes (eg . `#include "nodes/..."`)
- Toplevel citus includes, not contained in a directory (eg. `#include
"citus_verion.h"`)
- Columnar includes (eg. `#include "columnar/..."`)
- Distributed includes (eg. `#include "distributed/..."`)
Because it is quite hard to understand the difference between toplevel
citus includes and toplevel postgres includes it hardcodes the list of
toplevel citus includes. In the same manner it assumes anything not
prefixed with `columnar/` or `distributed/` as a postgres include.
The sorting/grouping is enforced by CI. Since we do so with our own
script there are not changes required in our uncrustify configuration.
With this PR, we allow creating distributed tables with without
specifying a shard key via create_distributed_table(). Here are the
the important details about those tables:
* Specifying `shard_count` is not allowed because it is assumed to be 1.
* We mostly call such tables as "null shard-key" table in code /
comments.
* To avoid doing a breaking layout change in create_distributed_table();
instead of throwing an error, it will inform the user that
`distribution_type`
param is ignored unless it's explicitly set to NULL or 'h'.
* `colocate_with` param allows colocating such null shard-key tables to
each other.
* We define this table type, i.e., NULL_SHARD_KEY_TABLE, as a subclass
of
DISTRIBUTED_TABLE because we mostly want to treat them as distributed
tables in terms of SQL / DDL / operation support.
* Metadata for such tables look like:
- distribution method => DISTRIBUTE_BY_NONE
- replication model => REPLICATION_MODEL_STREAMING
- colocation id => **!=** INVALID_COLOCATION_ID (distinguishes from
Citus local tables)
* We assign colocation groups for such tables to different nodes in a
round-robin fashion based on the modulo of "colocation id".
Note that this PR doesn't care about DDL (except CREATE TABLE) / SQL /
operation (i.e., Citus UDFs) support for such tables but adds a
preliminary
API.
Now that we will soon add another table type having DISTRIBUTE_BY_NONE
as distribution method and that we want the code to interpret such
tables mostly as distributed tables, let's make the definition of those
other two table types more strict by removing
CITUS_TABLE_WITH_NO_DIST_KEY
macro.
And instead, use HasDistributionKey() check in the places where the
logic applies to all table types that have / don't have a distribution
key. In future PRs, we might want to convert some of those
HasDistributionKey() checks if logic only applies to Citus local /
reference tables, not the others.
And adding HasDistributionKey() also allows us to consider having
DISTRIBUTE_BY_NONE as the distribution method as a "table attribute"
that can apply to distributed tables too, rather something that
determines the table type.
DESCRIPTION: Drop `SHARD_STATE_TO_DELETE` and use the cleanup records
instead
Drops the shard state that is used to mark shards as orphaned. Now we
insert cleanup records into `pg_dist_cleanup` so "orphaned" shards will
be dropped either by maintenance daemon or internal cleanup calls. With
this PR, we make the "cleanup orphaned shards" functions to be no-op, as
they would not be needed anymore.
This PR includes some naming changes about placement functions. We don't
need functions that filter orphaned shards, as there will be no orphaned
shards anymore.
We will also be introducing a small script with this PR, for users with
orphaned shards. We'll basically delete the orphaned shard entries from
`pg_dist_placement` and insert cleanup records into `pg_dist_cleanup`
for each one of them, during Citus upgrade.
We also have a lot of flakiness fixes in this PR.
Co-authored-by: Jelte Fennema <github-tech@jeltef.nl>
As of master branch, Citus does all the modifications to replicated tables
(e.g., reference tables and distributed tables with replication factor > 1),
via 2PC and avoids any shardstate=3. As a side-effect of those changes,
handling node failures for replicated tables change.
With this PR, when one (or multiple) node failures happen, the users would
see query errors on modifications. If the problem is intermitant, that's OK,
once the node failure(s) recover by themselves, the modification queries would
succeed. If the node failure(s) are permenant, the users should call
`SELECT citus_disable_node(...)` to disable the node. As soon as the node is
disabled, modification would start to succeed. However, now the old node gets
behind. It means that, when the node is up again, the placements should be
re-created on the node. First, use `SELECT citus_activate_node()`. Then, use
`SELECT replicate_table_shards(...)` to replicate the missing placements on
the re-activated node.
Ignore orphaned shards in more places
Only use active shard placements in RouterInsertTaskList
Use IncludingOrphanedPlacements in some more places
Fix comment
Add tests
Introduce table entry utility functions
Citus table cache entry utilities are introduced so that we can easily
extend existing functionality with minimum changes, specifically changes
to these functions. For example IsNonDistributedTableCacheEntry can be
extended for citus local tables without the need to scan the whole
codebase and update each relevant part.
* Introduce utility functions to find the type of tables
A table type can be a reference table, a hash/range/append distributed
table. Utility methods are created so that we don't have to worry about
how a table is considered as a reference table etc. This also makes it
easy to extend the table types.
* Add IsCitusTableType utilities
* Rename IsCacheEntryCitusTableType -> IsCitusTableTypeCacheEntry
* Change citus table types in some checks
* Use CalculateUniformHashRangeIndex in HashPartitionId
INT32_MIN definition can change among different platforms hence it is
possible to get overflow, we would see crashes because of this in debian
distros. We have already solved a similar problem with introducing
CalculateUniformHashRangeIndex method, hence to solve it we can use the
same method, this also removes some duplication and has a single place
to decide that.
* Use PG_INT32_XX instead of INT32_XX to be safer
Use partition column's collation for range distributed tables
Don't allow non deterministic collations for hash distributed tables
CoPartitionedTables: don't compare unequal types
With this commit, we all partitioned distributed tables with
replication factor > 1. However, we also have many restrictions.
In summary, we disallow all kinds of modifications (including DDLs)
on the partition tables. Instead, the user is allowed to run the
modifications over the parent table.
The necessity for such a restriction have two aspects:
- We need to acquire shard resource locks appropriately
- We need to handle marking partitions INVALID in case
of any failures. Note that, in theory, the parent table
should also become INVALID, which is too aggressive.
* Change worker_hash_partition_table() such that the
divergence between Citus planner's hashing and
worker_hash_partition_table() becomes the same.
* Rename single partitioning to single range partitioning.
* Add single hash repartitioning. Basically, logical planner
treats single hash and range partitioning almost equally.
Physical planner, on the other hand, treats single hash and
dual hash repartitioning almost equally (except for JoinPruning).
* Add a new GUC to enable this feature
ShardPlacementList's implementation can return NIL. In previous implementation
we got a segmentation fault in this case. The relation can be dropped after
getting distributed table list but before calling SingleReplicatedTable().
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.
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.
Renamed FindShardIntervalIndex() to ShardIndex() and added binary search
capability. It used to assume that hash partition tables are always
uniformly distributed which is not true if upcoming tenant isolation
feature is applied. This commit also reduces code duplication.
With this commit, we implemented some basic features of reference tables.
To start with, a reference table is
* a distributed table whithout a distribution column defined on it
* the distributed table is single sharded
* and the shard is replicated to all nodes
Reference tables follows the same code-path with a single sharded
tables. Thus, broadcast JOINs are applicable to reference tables.
But, since the table is replicated to all nodes, table fetching is
not required any more.
Reference tables support the uniqueness constraints for any column.
Reference tables can be used in INSERT INTO .. SELECT queries with
the following rules:
* If a reference table is in the SELECT part of the query, it is
safe join with another reference table and/or hash partitioned
tables.
* If a reference table is in the INSERT part of the query, all
other participating tables should be reference tables.
Reference tables follow the regular co-location structure. Since
all reference tables are single sharded and replicated to all nodes,
they are always co-located with each other.
Queries involving only reference tables always follows router planner
and executor.
Reference tables can have composite typed columns and there is no need
to create/define the necessary support functions.
All modification queries, master_* UDFs, EXPLAIN, DDLs, TRUNCATE,
sequences, transactions, COPY, schema support works on reference
tables as expected. Plus, all the pre-requisites associated with
distribution columns are dismissed.
With this change, we now push down foreign key constraints created during CREATE TABLE
statements. We also start to send foreign constraints during shard move along with
other DDL statements
Fixes#10
This change creates a new UDF: master_modify_multiple_shards
Parameters:
modify_query: A simple DELETE or UPDATE query as a string.
The UDF is similar to the existing master_apply_delete_command UDF.
Basically, given the modify query, it prunes the shard list, re-constructs
the query for each shard and sends the query to the placements.
Depending on the value of citus.multi_shard_commit_protocol, the commit
can be done in one-phase or two-phase manner.
Limitations:
* It cannot be called inside a transaction block
* It only be called with simple operator expressions (like Single Shard Modify)
Sample Usage:
```
SELECT master_modify_multiple_shards(
'DELETE FROM customer_delete_protocol WHERE c_custkey > 500 AND c_custkey < 500');
```
This commit adds a fast shard pruning path for INSERTs on
hash-partitioned tables. The rationale behind this change is
that if there exists a sorted shard interval array, a single
index lookup on the array allows us to find the corresponding
shard interval. As mentioned above, we need a sorted
(wrt shardminvalue) shard interval array. Thus, this commit
updates shardIntervalArray to sortedShardIntervalArray in the
metadata cache. Then uses the low-level API that is defined in
multi_copy to handle the fast shard pruning.
The performance impact of this change is more apparent as more
shards exist for a distributed table. Previous implementation
was relying on linear search through the shard intervals. However,
this commit relies on constant lookup time on shard interval
array. Thus, the shard pruning becomes less dependent on the
shard count.