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This commit fixes an ETS test case that tests the decentralized memory
counter in tables of type ordered_set with the write_concurrency
option turned on. The test case assumed that the memory consumption of
the table would only grow monotonically when terms are
inserted. However, this was not the case when the emulator was
compiled in debug mode as random splits and joins of CA tree nodes
could happen. This commit fixes the test case by disabling random
splits and joins in the tested table.
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Previously, all ETS tables used centralized counter variables to keep
track of the number of items stored and the amount of memory
consumed. These counters can cause scalability problems (especially on
big NUMA systems). This commit adds an implementation of a
decentralized counter and modifies the implementation of ETS so that
ETS tables of type ordered_set with write_concurrency enabled use the
decentralized counter. [Experiments][1] indicate that this change
substantially improves the scalability of ETS ordered_set tables with
write_concurrency enabled in scenarios with frequent `ets:insert/2`
and `ets:delete/2` calls.
The new counter is implemented in the module erts_flxctr
(`erts_flxctr.h` and `erts_flxctr.c`). The module has the suffix
flxctr as it contains the implementation of a flexible counter (i.e.,
counter instances can be configured to be either centralized or
decentralized). Counters that are configured to be centralized are
implemented with a single counter variable which is modified with
atomic operations. Decentralized counters are spread over several
cache lines (how many can be configured with the parameter
`+dcg`). The scheduler threads are mapped to cache lines so that there
is no single point of contention when decentralized counters are
updated. The thread progress functionality of the Erlang VM is
utilized to implement support for linearizable snapshots of
decentralized counters. The snapshot functionality is used by the
`ets:info/1` and `ets:info/2` functions.
[1]: http://winsh.me/ets_catree_benchmark/flxctr_res.html
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OTP-15610
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to easier generate a routing tree for test
without having to spend cpu to provoke actual repeated lock conflicts.
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Update table memory stats before scheduling free
to not be dependent on deallocation order with main table struct.
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The current ETS ordered_set implementation can quickly become a
scalability bottleneck on multicore machines when an application updates
an ordered_set table from concurrent processes [1][2]. The current
implementation is based on an AVL tree protected from concurrent writes
by a single readers-writer lock. Furthermore, the current implementation
has an optimization, called the stack optimization [3], that can improve
the performance when only a single process accesses a table but can
cause bad scalability even in read-only scenarios. It is possible to
pass the option {write_concurrency, true} to ets:new/2 when creating an
ETS table of type ordered_set but this option has no effect for tables
of type ordered_set without this commit. The new ETS ordered_set
implementation, added by this commit, is only activated when one passes
the options ordered_set and {write_concurrency, true} to the ets:new/2
function. Thus, the previous ordered_set implementation (from here on
called the default implementation) can still be used in applications
that do not benefit from the new implementation. The benchmark results
on the following web page show that the new implementation is many times
faster than the old implementation in some scenarios and that the old
implementation is still better than the new implementation in some
scenarios.
http://winsh.me/ets_catree_benchmark/ets_ca_tree_benchmark_results.html
The new implementation is expected to scale better than the default
implementation when concurrent processes use the following ETS
operations to operate on a table:
delete/2, delete_object/2, first/1, insert/2 (single object),
insert_new/2 (single object), lookup/2, lookup_element/2, member/2,
next/2, take/2 and update_element/3 (single object).
Currently, the new implementation does not have scalable support for the
other operations (e.g., select/2). However, when these operations are
used infrequently, the new implantation may still scale better than the
default implementation as the benchmark results at the URL above shows.
Description of the New Implementation
----------------------------------
The new implementation is based on a data structure which is called the
contention adapting search tree (CA tree for short). The following
publication contains a detailed description of the CA tree:
A Contention Adapting Approach to Concurrent Ordered Sets
Journal of Parallel and Distributed Computing, 2018
Kjell Winblad and Konstantinos Sagonas
https://doi.org/10.1016/j.jpdc.2017.11.007
http://www.it.uu.se/research/group/languages/software/ca_tree/catree_proofs.pdf
A discussion of how the CA tree can be used as an ETS back-end can be
found in another publication [1]. The CA tree is a data structure that
dynamically changes its synchronization granularity based on detected
contention. Internally, the CA tree uses instances of a sequential data
structure to store items. The CA tree implementation contained in this
commit uses the same AVL tree implementation as is used for the default
ordered set implementation. This AVL tree implementation is reused so
that much of the existing code to implement the ETS operations can be
reused.
Tests
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The ETS tests in `lib/stdlib/test/ets_SUITE.erl` have been extended to
also test the new ordered_set implementation. The function
ets_SUITE:throughput_benchmark/0 has also been added to this file. This
function can be used to measure and compare the performance of the
different ETS table types and options. This function writes benchmark
data to standard output that can be visualized by the HTML page
`lib/stdlib/test/ets_SUITE_data/visualize_throughput.html`.
[1]
More Scalable Ordered Set for ETS Using Adaptation.
In Thirteenth ACM SIGPLAN workshop on Erlang (2014).
Kjell Winblad and Konstantinos Sagonas.
https://doi.org/10.1145/2633448.2633455
http://www.it.uu.se/research/group/languages/software/ca_tree/erlang_paper.pdf
[2]
On the Scalability of the Erlang Term Storage
In Twelfth ACM SIGPLAN workshop on Erlang (2013)
Kjell Winblad, David Klaftenegger and Konstantinos Sagonas
https://doi.org/10.1145/2505305.2505308
http://winsh.me/papers/erlang_workshop_2013.pdf
[3]
The stack optimization works by keeping one preallocated stack instance
in every ordered_set table. This stack is updated so that it contains
the search path in some read operations (e.g., ets:next/2). This makes
it possible for a subsequent ets:next/2 to avoid traversing some nodes
in some cases. Unfortunately, the preallocated stack needs to be flagged
so that it is not updated concurrently by several threads which cause
bad scalability.
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by expanding the default size of the hash table
and increase number of locks.
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by using a cooperative strategy that will make
any process accessing the table execute delelete_all_objects_continue
until the table is empty.
This is not an optimal solution as concurrent threads will still
block on the table lock, but at least thread progress is made.
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and not the name. For more sane named table semantics.
Applies to both select/1 continuation and trap context.
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The implementation is still hidden behind ERTS_ENABLE_LOCK_COUNT, and
all categories are still enabled by default, but the actual counting can be
toggled at will.
OTP-13170
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from process psd through all owned/fixed tables.
As meta_pid_to{_fixed}_tab maps to slot in meta_main_tab
which is planned for destruction.
In this commit we no longer seize table lock while
freeing the table (free_table_cont) as it's not needed
and makes the code a bit simpler. Any concurrent operation
on the table will only access lock, owner and status
and then bail out.
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Instead of passing around a file descriptor
use a function pointer to facilitate more advanced
backend write logic such as size limitation or compression.
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due to the grow/shrink hysteresis of the meta tables
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* Keep it simple(r)
* To prepare for both dynamic sized segments and segtabs
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Conflicts:
erts/emulator/beam/erl_init.c
erts/etc/common/erlexec.c
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Add system_info(ets_limit) to provide a way to retrieve the runtime's
maximum number of ETS tables. Add tests and documentation for it too.
Also repair the alphabetical order of system_info/1 argument descriptions
in the documentation and in the erlang.erl clauses. Add new preloaded
erlang.erl due to that change. Also ensure all system_info/1 clauses are
represented in the erlang.xml source documentation -- a couple had been
inadvertently dropped in previous commits when other clauses were added.
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Functionality for scheduling operations at thread progress later
has been introduced.
Deallocation of ETS table structures were previously done by scheduling
misc aux work. Deallocation of process structures (not released yet)
was also implemented this way. Instead of using the misc aux work
functionality these implementation now use the newly introduced
functionality for scheduling operations at thread progress later. By
using this new functionaliy we reduce the amount of memory
allocation/deallocation operations needed.
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All uses of the old deprecated atomic API in the runtime system
have been replaced with the use of the new atomic API. In a lot of
places this change imply a relaxation of memory barriers used.
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The compressed format is using a slighty modified variant of the extern format
(term_to_binary). To not worsen key lookup's too much, the top tuple itself
and the key element are not compressed. Table objects with only immediate
non-key elements will therefor not gain anything (but actually consume one
extra word for "alloc_size").
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