TCP-H Test Report
Overview
To better understand the performance differences between StoneDB and ClickHouse as well as the performance of StoneDB, we use TPC-H to perform stress tests respectively on StoneDB and ClickHouse. The test data is 100 GB. The test process and the method used for calculating the test results fully comply with the requirements provided in tpc-h_v3.0.0, an official technical document of TPC-H.
TPC-H introduction
The TPC Benchmark-H (TPC-H) is a decision support benchmark. It consists of a suite of business-oriented ad-hoc queries and concurrent data modifications. The queries and the data populating the database have been chosen to have broad industry-wide relevance. The benchmark demonstrates decision support systems that:
- Examine large amounts of data.
- Execute queries with a high degree of complexity.
- Answer critical business questions.
TPC-H provides a series of SQL queries to test the performance of all kinds of decision-making support systems. These SQL queries are executed on standard databases with controlled conditions and have the following characteristics:
- Answer business questions.
- Are ad-hoc queries.
- Are more complicated that most OLTP transactions.
- Generate a large number of activities on databases deployed on the test system.
StoneDB introduction
StoneDB is an open-source hybrid transaction/analytical processing (HTAP) database designed and developed by StoneAtom based on the MySQL kernel. It is the first database of this type launched in China. StoneDB can be seamlessly switched from MySQL. It provides features such as optimal performance and real-time analytics, offering you a one-stop solution to process online transaction processing (OLTP), online analytical processing (OLAP), and HTAP workloads.
ClickHouse introduction
ClickHouse is a column-oriented database management system. It allows users to create tables and databases in runtime, and to load data and execute queries without reconfiguring and restarting the server. ClickHouse features linear scalability, easy-of-use, high reliability, and fault tolerance. It supports local attached storage so that it can be used to manage data at a larger scale. In addition, ClickHouse provides SQL interfaces for direct connection and native clients.
Test environment
The following table provides information about the test environment.
| Database | Deployment Mode | CPU | Memory | Version |
|---|---|---|---|---|
| StoneDB | Standalone | Intel(R) Xeon(R) CPU E5-2683 v4 @ 2.10GHz * 64 | 256 GB | 5.7_0.1 |
| ClickHouse | Standalone | Intel(R) Xeon(R) CPU E5-2683 v4 @ 2.10GHz * 64 | 256 GB | 22.5.1.2079 |
Test conclusion
The test data (100 GB), configuration, and SQL queries are the same. The 22 TPC-H SQL queries are executed respectively on StoneDB and ClickHouse to compare their performance.
The following table describes the test result.
| Metric | StoneDB | ClickHouse | Description |
|---|---|---|---|
| Total execution time (s) | 3387.86 | 11537.41 | A lower value indicates better performance. :::info The query speed of StoneDB is 3.4 times that of ClickHouse. ::: |
| Max. CPU time (%) | 5.27 | 50.24 | A lower value indicates better performance. :::info The max. CPU time spent on StoneDB is only one tenth that on ClickHouse.::: |
| Max. used memory (GB) | 90.36 | 123.8 | A lower value indicates better performance. :::info StoneDB saves 27% of memory, compared to ClickHouse. ::: |
| Max. write IOPS | 235.65 | 11.38 | A higher value indicates better performance. :::info The max. write IOPS of StoneDB is 20.70 times that of ClickHouse.::: |
| Max. read IOPS | 138.37 | 29.3 | A higher value indicates better performance. :::info The max. read IOPS of StoneDB is 4.72 times that of ClickHouse.::: |
| Max. system load in a minute | 8.77 | 34.96 | A lower value indicates better performance. :::info The max. system load in a minute on StoneDB is 25% that on ClickHouse.::: |
| Max. system load in 5 minutes | 3.30 | 32.85 | A lower value indicates better performance. :::info The max. system load in 5 minutes on StoneDB is only 10% that on ClickHouse.::: |
| Max. system load in 15 minutes | 2.08 | 32.20 | A lower value indicates better performance. :::info The max. system load in 15 minutes on StoneDB is only 6.5% that on ClickHouse.::: |
| Query success rate | 95% | 82% | A higher value indicates better performance. :::info The query success rate of StoneDB is 1.17 times that of ClickHouse.::: |
| Used disk space (GB) | 59 | 42 | A lower value indicates better performance. :::info ClickHouse saves 29% disk space, compared to StoneDB. ::: |
StoneDB performs better on all metrics, except the used disk space.
Test result details
Each SQL query is executed three times to obtain the average value of each performance metric. These average values are used for performance comparison between StoneDB and ClickHouse. The following table provides the execution time of each query.
| SQL | Execution time on StoneDB (s) | Execution time on ClickHouse (s) |
|---|---|---|
| 2 | 33.09 | 6859.13 |
| 3 | 88.22 | 178.56 |
| 4 | 75.92 | 176.19 |
| 5 | 168.75 | 342.97 |
| 6 | 7.90 | 0.26 |
| 7 | 390.29 | 290.51 |
| 8 | 108.98 | 1687.23 |
| 10 | 108.57 | 54.43 |
| 11 | 26.92 | 35.98 |
| 12 | 49.41 | 2.44 |
| 13 | 249.84 | 107.73 |
| 14 | 29.58 | 6.39 |
| 15 | 40.90 | 0.73 |
| 17 | 209.45 | 8.60 |
| 18 | 1101.70 | 518.54 |
| 20 | 130.90 | 27.51 |
| 21 | 567.46 | 1240.18 |
| Total | 3387.86 | 11537.41 |
info
Some SQL queries are timed out and therefore their execution time is not included in the values displayed in the Total row. The timed-out SQL queries are SQL 1, 9, 16, 19, and 22.
Procedure
Parameter settings for StoneDB:
root@stoneatom-02:~# cat /stonedb/install/stonedb.cnf
[client]
port = 3306
socket = /stonedb/install/tmp/mysql.sock
[mysqld]
port = 3306
basedir = /stonedb/install/
character-sets-dir = /stonedb/install/share/charsets/
lc-messages-dir = /stonedb/install/share/
plugin_dir = /stonedb/install/lib/plugin/
tmpdir = /stonedb/install/tmp/
socket = /stonedb/install/tmp/mysql.sock
datadir = /stonedb/install/data/
pid-file = /stonedb/install/data/mysqld.pid
log-error = /stonedb/install/log/mysqld.log
lc-messages-dir = /stonedb/install/share/english/
local-infile
stonedb_force_hashjoin=1
stonedb_join_parallel=0
stonedb_parallel_mapjoin=1
character-set-server = utf8mb4
collation-server = utf8mb4_general_ci
init_connect='SET NAMES utf8mb4'
#log-basename=mysqld
#debug-no-sync
# Retry bind as this may fail on busy server
#port-open-timeout=10
#plugin-load-add=ha_connect.so
max_connections=1000
explicit_defaults_for_timestamp = true
sql_mode='STRICT_TRANS_TABLES,NO_AUTO_CREATE_USER,NO_ENGINE_SUBSTITUTION'
tmp_table_size = 1024M
back_log = 130
#query_cache_size = 218M
#query_cache_type = 0
concurrent_insert=2
#deadlock_search_depth_short = 3
#deadlock_search_depth_long = 10
#deadlock_timeout_long = 10000000
#deadlock_timeout_short = 5000
slow-query-log = 1
slow_query_log_file=/stonedb/install/log/slow.log
#binlog config
long_query_time=5
max_binlog_size=1024M
sync_binlog=0
#log-bin=/stonedb/install/binlog/binlog
expire_logs_days=1
#log_bin_compress=1
#log_bin_compress_min_len=256
binlog_format=statement
binlog_cache_size = 524288
wait_timeout=3600
interactive_timeout=3600
connect_timeout=360
net_read_timeout=360
net_write_timeout=360
lock_wait_timeout=120
slave-net-timeout=120
skip-external-locking
skip-grant-tables
loose-key_buffer_size = 512M
max_allowed_packet = 512M
loose-sort_buffer_size = 4M
loose-read_buffer_size = 4M
loose-read_rnd_buffer_size = 16M
loose-thread_cache_size = 8
loose-query_cache_size = 0
# Try number of CPU's*2 for thread_concurrency
#thread_concurrency = 8
thread_stack = 512K
lower_case_table_names=0
group_concat_max_len=512
open_files_limit = 65535
server-id = 1
# Uncomment the following if you are using innodb tables
loose-innodb_data_home_dir = /stonedb/install/data/
loose-innodb_data_file_path = ibdata1:2000M;ibdata2:10M:autoextend
loose-innodb_buffer_pool_size= 512M
loose-innodb_lru_scan_depth= 100
loose-innodb_write_io_threads= 2
loose-innodb_read_io_threads= 2
loose-innodb_log_buffer_size= 1M
loose-innodb_log_file_size= 1024M
loose-innodb_log_files_in_group= 2
loose-innodb_log_group_home_dir = /stonedb/install/redolog/
loose-innodb-stats-persistent= OFF
loose-innodb_lock_wait_timeout = 50
loose-innodb_flush_method = O_DIRECT
loose-innodb_io_capacity = 500
loose-innodb_buffer_pool_dump_pct = 40
loose-innodb_print_all_deadlocks = 1
loose-innodb_undo_directory = /stonedb/install/undolog/
loose-innodb_undo_log_truncate = 1
loose-innodb_undo_tablespaces = 3
loose-innodb_undo_logs = 128
# MAINTAINER:
# the loose- syntax is to make sure the cnf file is also
# valid when building without the performance schema.
# Run tests with the performance schema instrumentation
loose-enable-performance-schema
# Run tests with a small number of instrumented objects
# to limit memory consumption with MTR
loose-performance-schema-accounts-size=100
loose-performance-schema-digests-size=200
loose-performance-schema-hosts-size=100
loose-performance-schema-users-size=100
loose-performance-schema-max-mutex-instances=5000
loose-performance-schema-max-rwlock-instances=5000
loose-performance-schema-max-cond-instances=1000
loose-performance-schema-max-file-instances=10000
loose-performance-schema-max-socket-instances=1000
loose-performance-schema-max-table-instances=500
loose-performance-schema-max-table-handles=1000
loose-performance-schema-events-waits-history-size=10
loose-performance-schema-events-waits-history-long-size=10000
loose-performance-schema-events-stages-history-size=10
loose-performance-schema-events-stages-history-long-size=1000
loose-performance-schema-events-statements-history-size=10
loose-performance-schema-events-statements-history-long-size=1000
loose-performance-schema-max-thread-instances=200
loose-performance-schema-session-connect-attrs-size=2048
# Enable everything, for maximun code exposure during testing
loose-performance-schema-instrument='%=ON'
loose-performance-schema-consumer-events-stages-current=ON
loose-performance-schema-consumer-events-stages-history=ON
loose-performance-schema-consumer-events-stages-history-long=ON
loose-performance-schema-consumer-events-statements-current=ON
loose-performance-schema-consumer-events-statements-history=ON
loose-performance-schema-consumer-events-statements-history-long=ON
loose-performance-schema-consumer-events-waits-current=ON
loose-performance-schema-consumer-events-waits-history=ON
loose-performance-schema-consumer-events-waits-history-long=ON
loose-performance-schema-consumer-global-instrumentation=ON
loose-performance-schema-consumer-thread-instrumentation=ON
binlog-direct-non-transactional-updates
default-storage-engine=MyISAM
#use_stat_tables=preferably
# here, at the end of [mysqld] group mtr will automatically disable
# all optional plugins.
[embedded]
# mtr automatically adds [embedded] group at the end and copies [mysqld]
# and [mysqld.1] groups into it.
# but we want [server] group to be after [mysqld] (and its copies).
# create a non-empty [embedded] group here, to force it before [server]
local-infile
[server]
# Aria is optional, but it must be enabled if it's used for temporary
# tables. Let's enable it in the [server] group, because this group
# is read after [mysqld] and [embedded]
#loose-loog
[connection]
default-character-set=utf8mb4
[mysqldump]
quick
max_allowed_packet = 512M
[mysql]
no-auto-rehash
# Remove the next comment character if you are not familiar with SQL
#safe-updates
no-auto-rehash
max_allowed_packet=128M
prompt='\u@\h [\d]> '
default_character_set=utf8
[isamchk]
key_buffer_size = 256M
sort_buffer_size = 256M
read_buffer = 2M
write_buffer = 2M
[mysqlhotcopy]
interactive-timeout
Parameter settings for ClickHouse, which is saved in etc/clickhouse-server/config.xml:
<?xml version="1.0"?>
<!--
NOTE: User and query level settings are set up in "users.xml" file.
If you have accidentally specified user-level settings here, server won't start.
You can either move the settings to the right place inside "users.xml" file
or add <skip_check_for_incorrect_settings>1</skip_check_for_incorrect_settings> here.
-->
<clickhouse>
<logger>
<!-- Possible levels [1]:
- none (turns off logging)
- fatal
- critical
- error
- warning
- notice
- information
- debug
- trace
- test (not for production usage)
[1]: https://github.com/pocoproject/poco/blob/poco-1.9.4-release/Foundation/include/Poco/Logger.h#L105-L114
-->
<level>trace</level>
<log>/var/log/clickhouse-server/clickhouse-server.log</log>
<errorlog>/var/log/clickhouse-server/clickhouse-server.err.log</errorlog>
<!-- Rotation policy
See https://github.com/pocoproject/poco/blob/poco-1.9.4-release/Foundation/include/Poco/FileChannel.h#L54-L85
-->
<size>1000M</size>
<count>10</count>
<!-- <console>1</console> --> <!-- Default behavior is autodetection (log to console if not daemon mode and is tty) -->
<!-- Per level overrides (legacy):
For example to suppress logging of the ConfigReloader you can use:
NOTE: levels.logger is reserved, see below.
-->
<!--
<levels>
<ConfigReloader>none</ConfigReloader>
</levels>
-->
<!-- Per level overrides:
For example to suppress logging of the RBAC for default user you can use:
(But please note that the logger name maybe changed from version to version, even after minor upgrade)
-->
<!--
<levels>
<logger>
<name>ContextAccess (default)</name>
<level>none</level>
</logger>
<logger>
<name>DatabaseOrdinary (test)</name>
<level>none</level>
</logger>
</levels>
-->
</logger>
<!-- Add headers to response in options request. OPTIONS method is used in CORS preflight requests. -->
<!-- It is off by default. Next headers are obligate for CORS.-->
<!-- http_options_response>
<header>
<name>Access-Control-Allow-Origin</name>
<value>*</value>
</header>
<header>
<name>Access-Control-Allow-Headers</name>
<value>origin, x-requested-with</value>
</header>
<header>
<name>Access-Control-Allow-Methods</name>
<value>POST, GET, OPTIONS</value>
</header>
<header>
<name>Access-Control-Max-Age</name>
<value>86400</value>
</header>
</http_options_response -->
<!-- It is the name that will be shown in the clickhouse-client.
By default, anything with "production" will be highlighted in red in query prompt.
-->
<!--display_name>production</display_name-->
<!-- Port for HTTP API. See also 'https_port' for secure connections.
This interface is also used by ODBC and JDBC drivers (DataGrip, Dbeaver, ...)
and by most of web interfaces (embedded UI, Grafana, Redash, ...).
-->
<http_port>8123</http_port>
<!-- Port for interaction by native protocol with:
- clickhouse-client and other native ClickHouse tools (clickhouse-benchmark, clickhouse-copier);
- clickhouse-server with other clickhouse-servers for distributed query processing;
- ClickHouse drivers and applications supporting native protocol
(this protocol is also informally called as "the TCP protocol");
See also 'tcp_port_secure' for secure connections.
-->
<tcp_port>9000</tcp_port>
<!-- Compatibility with MySQL protocol.
ClickHouse will pretend to be MySQL for applications connecting to this port.
-->
<mysql_port>9004</mysql_port>
<!-- Compatibility with PostgreSQL protocol.
ClickHouse will pretend to be PostgreSQL for applications connecting to this port.
-->
<postgresql_port>9005</postgresql_port>
<!-- HTTP API with TLS (HTTPS).
You have to configure certificate to enable this interface.
See the openSSL section below.
-->
<!-- <https_port>8443</https_port> -->
<!-- Native interface with TLS.
You have to configure certificate to enable this interface.
See the openSSL section below.
-->
<!-- <tcp_port_secure>9440</tcp_port_secure> -->
<!-- Native interface wrapped with PROXYv1 protocol
PROXYv1 header sent for every connection.
ClickHouse will extract information about proxy-forwarded client address from the header.
-->
<!-- <tcp_with_proxy_port>9011</tcp_with_proxy_port> -->
<!-- Port for communication between replicas. Used for data exchange.
It provides low-level data access between servers.
This port should not be accessible from untrusted networks.
See also 'interserver_http_credentials'.
Data transferred over connections to this port should not go through untrusted networks.
See also 'interserver_https_port'.
-->
<interserver_http_port>9009</interserver_http_port>
<!-- Port for communication between replicas with TLS.
You have to configure certificate to enable this interface.
See the openSSL section below.
See also 'interserver_http_credentials'.
-->
<!-- <interserver_https_port>9010</interserver_https_port> -->
<!-- Hostname that is used by other replicas to request this server.
If not specified, then it is determined analogous to 'hostname -f' command.
This setting could be used to switch replication to another network interface
(the server may be connected to multiple networks via multiple addresses)
-->
<!--
<interserver_http_host>example.clickhouse.com</interserver_http_host>
-->
<!-- You can specify credentials for authenthication between replicas.
This is required when interserver_https_port is accessible from untrusted networks,
and also recommended to avoid SSRF attacks from possibly compromised services in your network.
-->
<!--<interserver_http_credentials>
<user>interserver</user>
<password></password>
</interserver_http_credentials>-->
<!-- Listen specified address.
Use :: (wildcard IPv6 address), if you want to accept connections both with IPv4 and IPv6 from everywhere.
Notes:
If you open connections from wildcard address, make sure that at least one of the following measures applied:
- server is protected by firewall and not accessible from untrusted networks;
- all users are restricted to subset of network addresses (see users.xml);
- all users have strong passwords, only secure (TLS) interfaces are accessible, or connections are only made via TLS interfaces.
- users without password have readonly access.
See also: https://www.shodan.io/search?query=clickhouse
-->
<!-- <listen_host>::</listen_host> -->
<listen_host>::</listen_host>
<!-- Same for hosts without support for IPv6: -->
<!-- <listen_host>0.0.0.0</listen_host> -->
<!-- Default values - try listen localhost on IPv4 and IPv6. -->
<!--
<listen_host>::1</listen_host>
<listen_host>127.0.0.1</listen_host>
-->
<!-- Don't exit if IPv6 or IPv4 networks are unavailable while trying to listen. -->
<!-- <listen_try>0</listen_try> -->
<!-- Allow multiple servers to listen on the same address:port. This is not recommended.
-->
<!-- <listen_reuse_port>0</listen_reuse_port> -->
<!-- <listen_backlog>4096</listen_backlog> -->
<max_connections>4096</max_connections>
<!-- For 'Connection: keep-alive' in HTTP 1.1 -->
<keep_alive_timeout>3</keep_alive_timeout>
<!-- gRPC protocol (see src/Server/grpc_protos/clickhouse_grpc.proto for the API) -->
<!-- <grpc_port>9100</grpc_port> -->
<grpc>
<enable_ssl>false</enable_ssl>
<!-- The following two files are used only if enable_ssl=1 -->
<ssl_cert_file>/path/to/ssl_cert_file</ssl_cert_file>
<ssl_key_file>/path/to/ssl_key_file</ssl_key_file>
<!-- Whether server will request client for a certificate -->
<ssl_require_client_auth>false</ssl_require_client_auth>
<!-- The following file is used only if ssl_require_client_auth=1 -->
<ssl_ca_cert_file>/path/to/ssl_ca_cert_file</ssl_ca_cert_file>
<!-- Default transport compression type (can be overridden by client, see the transport_compression_type field in QueryInfo).
Supported algorithms: none, deflate, gzip, stream_gzip -->
<transport_compression_type>none</transport_compression_type>
<!-- Default transport compression level. Supported levels: 0..3 -->
<transport_compression_level>0</transport_compression_level>
<!-- Send/receive message size limits in bytes. -1 means unlimited -->
<max_send_message_size>-1</max_send_message_size>
<max_receive_message_size>-1</max_receive_message_size>
<!-- Enable if you want very detailed logs -->
<verbose_logs>false</verbose_logs>
</grpc>
<!-- Used with https_port and tcp_port_secure. Full ssl options list: https://github.com/ClickHouse-Extras/poco/blob/master/NetSSL_OpenSSL/include/Poco/Net/SSLManager.h#L71 -->
<openSSL>
<server> <!-- Used for https server AND secure tcp port -->
<!-- openssl req -subj "/CN=localhost" -new -newkey rsa:2048 -days 365 -nodes -x509 -keyout /etc/clickhouse-server/server.key -out /etc/clickhouse-server/server.crt -->
<!-- <certificateFile>/etc/clickhouse-server/server.crt</certificateFile>
<privateKeyFile>/etc/clickhouse-server/server.key</privateKeyFile> -->
<!-- dhparams are optional. You can delete the <dhParamsFile> element.
To generate dhparams, use the following command:
openssl dhparam -out /etc/clickhouse-server/dhparam.pem 4096
Only file format with BEGIN DH PARAMETERS is supported.
-->
<!-- <dhParamsFile>/etc/clickhouse-server/dhparam.pem</dhParamsFile>-->
<verificationMode>none</verificationMode>
<loadDefaultCAFile>true</loadDefaultCAFile>
<cacheSessions>true</cacheSessions>
<disableProtocols>sslv2,sslv3</disableProtocols>
<preferServerCiphers>true</preferServerCiphers>
</server>
<client> <!-- Used for connecting to https dictionary source and secured Zookeeper communication -->
<loadDefaultCAFile>true</loadDefaultCAFile>
<cacheSessions>true</cacheSessions>
<disableProtocols>sslv2,sslv3</disableProtocols>
<preferServerCiphers>true</preferServerCiphers>
<!-- Use for self-signed: <verificationMode>none</verificationMode> -->
<invalidCertificateHandler>
<!-- Use for self-signed: <name>AcceptCertificateHandler</name> -->
<name>RejectCertificateHandler</name>
</invalidCertificateHandler>
</client>
</openSSL>
<!-- Default root page on http[s] server. For example load UI from https://tabix.io/ when opening http://localhost:8123 -->
<!--
<http_server_default_response><![CDATA[<html ng-app="SMI2"><head><base href="http://ui.tabix.io/"></head><body><div ui-view="" class="content-ui"></div><script src="http://loader.tabix.io/master.js"></script></body></html>]]></http_server_default_response>
-->
<!-- Maximum number of concurrent queries. -->
<max_concurrent_queries>100</max_concurrent_queries>
<!-- Maximum memory usage (resident set size) for server process.
Zero value or unset means default. Default is "max_server_memory_usage_to_ram_ratio" of available physical RAM.
If the value is larger than "max_server_memory_usage_to_ram_ratio" of available physical RAM, it will be cut down.
The constraint is checked on query execution time.
If a query tries to allocate memory and the current memory usage plus allocation is greater
than specified threshold, exception will be thrown.
It is not practical to set this constraint to small values like just a few gigabytes,
because memory allocator will keep this amount of memory in caches and the server will deny service of queries.
-->
<max_server_memory_usage>0</max_server_memory_usage>
<!-- Maximum number of threads in the Global thread pool.
This will default to a maximum of 10000 threads if not specified.
This setting will be useful in scenarios where there are a large number
of distributed queries that are running concurrently but are idling most
of the time, in which case a higher number of threads might be required.
-->
<max_thread_pool_size>10000</max_thread_pool_size>
<!-- Number of workers to recycle connections in background (see also drain_timeout).
If the pool is full, connection will be drained synchronously. -->
<!-- <max_threads_for_connection_collector>10</max_threads_for_connection_collector> -->
<!-- On memory constrained environments you may have to set this to value larger than 1.
-->
<max_server_memory_usage_to_ram_ratio>0.9</max_server_memory_usage_to_ram_ratio>
<!-- Simple server-wide memory profiler. Collect a stack trace at every peak allocation step (in bytes).
Data will be stored in system.trace_log table with query_id = empty string.
Zero means disabled.
-->
<total_memory_profiler_step>4194304</total_memory_profiler_step>
<!-- Collect random allocations and deallocations and write them into system.trace_log with 'MemorySample' trace_type.
The probability is for every alloc/free regardless to the size of the allocation.
Note that sampling happens only when the amount of untracked memory exceeds the untracked memory limit,
which is 4 MiB by default but can be lowered if 'total_memory_profiler_step' is lowered.
You may want to set 'total_memory_profiler_step' to 1 for extra fine grained sampling.
-->
<total_memory_tracker_sample_probability>0</total_memory_tracker_sample_probability>
<!-- Set limit on number of open files (default: maximum). This setting makes sense on Mac OS X because getrlimit() fails to retrieve
correct maximum value. -->
<!-- <max_open_files>262144</max_open_files> -->
<!-- Size of cache of uncompressed blocks of data, used in tables of MergeTree family.
In bytes. Cache is single for server. Memory is allocated only on demand.
Cache is used when 'use_uncompressed_cache' user setting turned on (off by default).
Uncompressed cache is advantageous only for very short queries and in rare cases.
Note: uncompressed cache can be pointless for lz4, because memory bandwidth
is slower than multi-core decompression on some server configurations.
Enabling it can sometimes paradoxically make queries slower.
-->
<uncompressed_cache_size>8589934592</uncompressed_cache_size>
<!-- Approximate size of mark cache, used in tables of MergeTree family.
In bytes. Cache is single for server. Memory is allocated only on demand.
You should not lower this value.
-->
<mark_cache_size>5368709120</mark_cache_size>
<!-- If you enable the `min_bytes_to_use_mmap_io` setting,
the data in MergeTree tables can be read with mmap to avoid copying from kernel to userspace.
It makes sense only for large files and helps only if data reside in page cache.
To avoid frequent open/mmap/munmap/close calls (which are very expensive due to consequent page faults)
and to reuse mappings from several threads and queries,
the cache of mapped files is maintained. Its size is the number of mapped regions (usually equal to the number of mapped files).
The amount of data in mapped files can be monitored
in system.metrics, system.metric_log by the MMappedFiles, MMappedFileBytes metrics
and in system.asynchronous_metrics, system.asynchronous_metrics_log by the MMapCacheCells metric,
and also in system.events, system.processes, system.query_log, system.query_thread_log, system.query_views_log by the
CreatedReadBufferMMap, CreatedReadBufferMMapFailed, MMappedFileCacheHits, MMappedFileCacheMisses events.
Note that the amount of data in mapped files does not consume memory directly and is not accounted
in query or server memory usage - because this memory can be discarded similar to OS page cache.
The cache is dropped (the files are closed) automatically on removal of old parts in MergeTree,
also it can be dropped manually by the SYSTEM DROP MMAP CACHE query.
-->
<mmap_cache_size>1000</mmap_cache_size>
<!-- Cache size in bytes for compiled expressions.-->
<compiled_expression_cache_size>134217728</compiled_expression_cache_size>
<!-- Cache size in elements for compiled expressions.-->
<compiled_expression_cache_elements_size>10000</compiled_expression_cache_elements_size>
<!-- Path to data directory, with trailing slash. -->
<path>/data/clickhouse/</path>
<!-- Path to temporary data for processing hard queries. -->
<tmp_path>/data/clickhouse/tmp/</tmp_path>
<!-- Disable AuthType plaintext_password and no_password for ACL. -->
<!-- <allow_plaintext_password>0</allow_plaintext_password> -->
<!-- <allow_no_password>0</allow_no_password> -->`
<!-- Policy from the <storage_configuration> for the temporary files.
If not set <tmp_path> is used, otherwise <tmp_path> is ignored.
Notes:
- move_factor is ignored
- keep_free_space_bytes is ignored
- max_data_part_size_bytes is ignored
- you must have exactly one volume in that policy
-->
<!-- <tmp_policy>tmp</tmp_policy> -->
<!-- Directory with user provided files that are accessible by 'file' table function. -->
<user_files_path>/data/clickhouse/user_files/</user_files_path>
<!-- LDAP server definitions. -->
<ldap_servers>
<!-- List LDAP servers with their connection parameters here to later 1) use them as authenticators for dedicated local users,
who have 'ldap' authentication mechanism specified instead of 'password', or to 2) use them as remote user directories.
Parameters:
host - LDAP server hostname or IP, this parameter is mandatory and cannot be empty.
port - LDAP server port, default is 636 if enable_tls is set to true, 389 otherwise.
bind_dn - template used to construct the DN to bind to.
The resulting DN will be constructed by replacing all '{user_name}' substrings of the template with the actual
user name during each authentication attempt.
user_dn_detection - section with LDAP search parameters for detecting the actual user DN of the bound user.
This is mainly used in search filters for further role mapping when the server is Active Directory. The
resulting user DN will be used when replacing '{user_dn}' substrings wherever they are allowed. By default,
user DN is set equal to bind DN, but once search is performed, it will be updated with to the actual detected
user DN value.
base_dn - template used to construct the base DN for the LDAP search.
The resulting DN will be constructed by replacing all '{user_name}' and '{bind_dn}' substrings
of the template with the actual user name and bind DN during the LDAP search.
scope - scope of the LDAP search.
Accepted values are: 'base', 'one_level', 'children', 'subtree' (the default).
search_filter - template used to construct the search filter for the LDAP search.
The resulting filter will be constructed by replacing all '{user_name}', '{bind_dn}', and '{base_dn}'
substrings of the template with the actual user name, bind DN, and base DN during the LDAP search.
Note, that the special characters must be escaped properly in XML.
verification_cooldown - a period of time, in seconds, after a successful bind attempt, during which a user will be assumed
to be successfully authenticated for all consecutive requests without contacting the LDAP server.
Specify 0 (the default) to disable caching and force contacting the LDAP server for each authentication request.
enable_tls - flag to trigger use of secure connection to the LDAP server.
Specify 'no' for plain text (ldap://) protocol (not recommended).
Specify 'yes' for LDAP over SSL/TLS (ldaps://) protocol (recommended, the default).
Specify 'starttls' for legacy StartTLS protocol (plain text (ldap://) protocol, upgraded to TLS).
tls_minimum_protocol_version - the minimum protocol version of SSL/TLS.
Accepted values are: 'ssl2', 'ssl3', 'tls1.0', 'tls1.1', 'tls1.2' (the default).
tls_require_cert - SSL/TLS peer certificate verification behavior.
Accepted values are: 'never', 'allow', 'try', 'demand' (the default).
tls_cert_file - path to certificate file.
tls_key_file - path to certificate key file.
tls_ca_cert_file - path to CA certificate file.
tls_ca_cert_dir - path to the directory containing CA certificates.
tls_cipher_suite - allowed cipher suite (in OpenSSL notation).
Example:
<my_ldap_server>
<host>localhost</host>
<port>636</port>
<bind_dn>uid={user_name},ou=users,dc=example,dc=com</bind_dn>
<verification_cooldown>300</verification_cooldown>
<enable_tls>yes</enable_tls>
<tls_minimum_protocol_version>tls1.2</tls_minimum_protocol_version>
<tls_require_cert>demand</tls_require_cert>
<tls_cert_file>/path/to/tls_cert_file</tls_cert_file>
<tls_key_file>/path/to/tls_key_file</tls_key_file>
<tls_ca_cert_file>/path/to/tls_ca_cert_file</tls_ca_cert_file>
<tls_ca_cert_dir>/path/to/tls_ca_cert_dir</tls_ca_cert_dir>
<tls_cipher_suite>ECDHE-ECDSA-AES256-GCM-SHA384:ECDHE-RSA-AES256-GCM-SHA384:AES256-GCM-SHA384</tls_cipher_suite>
</my_ldap_server>
Example (typical Active Directory with configured user DN detection for further role mapping):
<my_ad_server>
<host>localhost</host>
<port>389</port>
<bind_dn>EXAMPLE\{user_name}</bind_dn>
<user_dn_detection>
<base_dn>CN=Users,DC=example,DC=com</base_dn>
<search_filter>(&(objectClass=user)(sAMAccountName={user_name}))</search_filter>
</user_dn_detection>
<enable_tls>no</enable_tls>
</my_ad_server>
-->
</ldap_servers>
<!-- To enable Kerberos authentication support for HTTP requests (GSS-SPNEGO), for those users who are explicitly configured
to authenticate via Kerberos, define a single 'kerberos' section here.
Parameters:
principal - canonical service principal name, that will be acquired and used when accepting security contexts.
This parameter is optional, if omitted, the default principal will be used.
This parameter cannot be specified together with 'realm' parameter.
realm - a realm, that will be used to restrict authentication to only those requests whose initiator's realm matches it.
This parameter is optional, if omitted, no additional filtering by realm will be applied.
This parameter cannot be specified together with 'principal' parameter.
Example:
<kerberos />
Example:
<kerberos>
<principal>HTTP/clickhouse.example.com@EXAMPLE.COM</principal>
</kerberos>
Example:
<kerberos>
<realm>EXAMPLE.COM</realm>
</kerberos>
-->
<!-- Sources to read users, roles, access rights, profiles of settings, quotas. -->
<user_directories>
<users_xml>
<!-- Path to configuration file with predefined users. -->
<path>users.xml</path>
</users_xml>
<local_directory>
<!-- Path to folder where users created by SQL commands are stored. -->
<path>/data/clickhouse/access/</path>
</local_directory>
<!-- To add an LDAP server as a remote user directory of users that are not defined locally, define a single 'ldap' section
with the following parameters:
server - one of LDAP server names defined in 'ldap_servers' config section above.
This parameter is mandatory and cannot be empty.
roles - section with a list of locally defined roles that will be assigned to each user retrieved from the LDAP server.
If no roles are specified here or assigned during role mapping (below), user will not be able to perform any
actions after authentication.
role_mapping - section with LDAP search parameters and mapping rules.
When a user authenticates, while still bound to LDAP, an LDAP search is performed using search_filter and the
name of the logged in user. For each entry found during that search, the value of the specified attribute is
extracted. For each attribute value that has the specified prefix, the prefix is removed, and the rest of the
value becomes the name of a local role defined in ClickHouse, which is expected to be created beforehand by
CREATE ROLE command.
There can be multiple 'role_mapping' sections defined inside the same 'ldap' section. All of them will be
applied.
base_dn - template used to construct the base DN for the LDAP search.
The resulting DN will be constructed by replacing all '{user_name}', '{bind_dn}', and '{user_dn}'
substrings of the template with the actual user name, bind DN, and user DN during each LDAP search.
scope - scope of the LDAP search.
Accepted values are: 'base', 'one_level', 'children', 'subtree' (the default).
search_filter - template used to construct the search filter for the LDAP search.
The resulting filter will be constructed by replacing all '{user_name}', '{bind_dn}', '{user_dn}', and
'{base_dn}' substrings of the template with the actual user name, bind DN, user DN, and base DN during
each LDAP search.
Note, that the special characters must be escaped properly in XML.
attribute - attribute name whose values will be returned by the LDAP search. 'cn', by default.
prefix - prefix, that will be expected to be in front of each string in the original list of strings returned by
the LDAP search. Prefix will be removed from the original strings and resulting strings will be treated
as local role names. Empty, by default.
Example:
<ldap>
<server>my_ldap_server</server>
<roles>
<my_local_role1 />
<my_local_role2 />
</roles>
<role_mapping>
<base_dn>ou=groups,dc=example,dc=com</base_dn>
<scope>subtree</scope>
<search_filter>(&(objectClass=groupOfNames)(member={bind_dn}))</search_filter>
<attribute>cn</attribute>
<prefix>clickhouse_</prefix>
</role_mapping>
</ldap>
Example (typical Active Directory with role mapping that relies on the detected user DN):
<ldap>
<server>my_ad_server</server>
<role_mapping>
<base_dn>CN=Users,DC=example,DC=com</base_dn>
<attribute>CN</attribute>
<scope>subtree</scope>
<search_filter>(&(objectClass=group)(member={user_dn}))</search_filter>
<prefix>clickhouse_</prefix>
</role_mapping>
</ldap>
-->
</user_directories>
<access_control_improvements>
<!-- Enables logic that users without permissive row policies can still read rows using a SELECT query.
For example, if there two users A, B and a row policy is defined only for A, then
if this setting is true the user B will see all rows, and if this setting is false the user B will see no rows.
By default this setting is false for compatibility with earlier access configurations. -->
<users_without_row_policies_can_read_rows>false</users_without_row_policies_can_read_rows>
</access_control_improvements>
<!-- Default profile of settings. -->
<default_profile>default</default_profile>
<!-- Comma-separated list of prefixes for user-defined settings. -->
<custom_settings_prefixes></custom_settings_prefixes>
<!-- System profile of settings. This settings are used by internal processes (Distributed DDL worker and so on). -->
<!-- <system_profile>default</system_profile> -->
<!-- Buffer profile of settings.
This settings are used by Buffer storage to flush data to the underlying table.
Default: used from system_profile directive.
-->
<!-- <buffer_profile>default</buffer_profile> -->
<!-- Default database. -->
<default_database>default</default_database>
<!-- Server time zone could be set here.
Time zone is used when converting between String and DateTime types,
when printing DateTime in text formats and parsing DateTime from text,
it is used in date and time related functions, if specific time zone was not passed as an argument.
Time zone is specified as identifier from IANA time zone database, like UTC or Africa/Abidjan.
If not specified, system time zone at server startup is used.
Please note, that server could display time zone alias instead of specified name.
Example: Zulu is an alias for UTC.
-->
<!-- <timezone>UTC</timezone> -->
<!-- You can specify umask here (see "man umask"). Server will apply it on startup.
Number is always parsed as octal. Default umask is 027 (other users cannot read logs, data files, etc; group can only read).
-->
<!-- <umask>022</umask> -->
<!-- Perform mlockall after startup to lower first queries latency
and to prevent clickhouse executable from being paged out under high IO load.
Enabling this option is recommended but will lead to increased startup time for up to a few seconds.
-->
<mlock_executable>true</mlock_executable>
<!-- Reallocate memory for machine code ("text") using huge pages. Highly experimental. -->
<remap_executable>false</remap_executable>
<![CDATA[
Uncomment below in order to use JDBC table engine and function.
To install and run JDBC bridge in background:
* [Debian/Ubuntu]
export MVN_URL=https://repo1.maven.org/maven2/com/clickhouse/clickhouse-jdbc-bridge/
export PKG_VER=$(curl -sL $MVN_URL/maven-metadata.xml | grep '<release>' | sed -e 's|.*>\(.*\)<.*|\1|')
wget https://github.com/ClickHouse/clickhouse-jdbc-bridge/releases/download/v$PKG_VER/clickhouse-jdbc-bridge_$PKG_VER-1_all.deb
apt install --no-install-recommends -f ./clickhouse-jdbc-bridge_$PKG_VER-1_all.deb
clickhouse-jdbc-bridge &
* [CentOS/RHEL]
export MVN_URL=https://repo1.maven.org/maven2/com/clickhouse/clickhouse-jdbc-bridge/
export PKG_VER=$(curl -sL $MVN_URL/maven-metadata.xml | grep '<release>' | sed -e 's|.*>\(.*\)<.*|\1|')
wget https://github.com/ClickHouse/clickhouse-jdbc-bridge/releases/download/v$PKG_VER/clickhouse-jdbc-bridge-$PKG_VER-1.noarch.rpm
yum localinstall -y clickhouse-jdbc-bridge-$PKG_VER-1.noarch.rpm
clickhouse-jdbc-bridge &
Please refer to https://github.com/ClickHouse/clickhouse-jdbc-bridge#usage for more information.
]]>
<!--
<jdbc_bridge>
<host>127.0.0.1</host>
<port>9019</port>
</jdbc_bridge>
-->
<!-- Configuration of clusters that could be used in Distributed tables.
https://clickhouse.com/docs/en/operations/table_engines/distributed/
-->
<remote_servers>
<!-- Test only shard config for testing distributed storage -->
<test_shard_localhost>
<!-- Inter-server per-cluster secret for Distributed queries
default: no secret (no authentication will be performed)
If set, then Distributed queries will be validated on shards, so at least:
- such cluster should exist on the shard,
- such cluster should have the same secret.
And also (and which is more important), the initial_user will
be used as current user for the query.
Right now the protocol is pretty simple and it only takes into account:
- cluster name
- query
Also it will be nice if the following will be implemented:
- source hostname (see interserver_http_host), but then it will depends from DNS,
it can use IP address instead, but then the you need to get correct on the initiator node.
- target hostname / ip address (same notes as for source hostname)
- time-based security tokens
-->
<!-- <secret></secret> -->
<shard>
<!-- Optional. Whether to write data to just one of the replicas. Default: false (write data to all replicas). -->
<!-- <internal_replication>false</internal_replication> -->
<!-- Optional. Shard weight when writing data. Default: 1. -->
<!-- <weight>1</weight> -->
<replica>
<host>localhost</host>
<port>9000</port>
<!-- Optional. Priority of the replica for load_balancing. Default: 1 (less value has more priority). -->
<!-- <priority>1</priority> -->
</replica>
</shard>
</test_shard_localhost>
<test_cluster_one_shard_three_replicas_localhost>
<shard>
<internal_replication>false</internal_replication>
<replica>
<host>127.0.0.1</host>
<port>9000</port>
</replica>
<replica>
<host>127.0.0.2</host>
<port>9000</port>
</replica>
<replica>
<host>127.0.0.3</host>
<port>9000</port>
</replica>
</shard>
<!--shard>
<internal_replication>false</internal_replication>
<replica>
<host>127.0.0.1</host>
<port>9000</port>
</replica>
<replica>
<host>127.0.0.2</host>
<port>9000</port>
</replica>
<replica>
<host>127.0.0.3</host>
<port>9000</port>
</replica>
</shard-->
</test_cluster_one_shard_three_replicas_localhost>
<test_cluster_two_shards_localhost>
<shard>
<replica>
<host>localhost</host>
<port>9000</port>
</replica>
</shard>
<shard>
<replica>
<host>localhost</host>
<port>9000</port>
</replica>
</shard>
</test_cluster_two_shards_localhost>
<test_cluster_two_shards>
<shard>
<replica>
<host>127.0.0.1</host>
<port>9000</port>
</replica>
</shard>
<shard>
<replica>
<host>127.0.0.2</host>
<port>9000</port>
</replica>
</shard>
</test_cluster_two_shards>
<test_cluster_two_shards_internal_replication>
<shard>
<internal_replication>true</internal_replication>
<replica>
<host>127.0.0.1</host>
<port>9000</port>
</replica>
</shard>
<shard>
<internal_replication>true</internal_replication>
<replica>
<host>127.0.0.2</host>
<port>9000</port>
</replica>
</shard>
</test_cluster_two_shards_internal_replication>
<test_shard_localhost_secure>
<shard>
<replica>
<host>localhost</host>
<port>9440</port>
<secure>1</secure>
</replica>
</shard>
</test_shard_localhost_secure>
<test_unavailable_shard>
<shard>
<replica>
<host>localhost</host>
<port>9000</port>
</replica>
</shard>
<shard>
<replica>
<host>localhost</host>
<port>1</port>
</replica>
</shard>
</test_unavailable_shard>
</remote_servers>
<!-- The list of hosts allowed to use in URL-related storage engines and table functions.
If this section is not present in configuration, all hosts are allowed.
-->
<!--<remote_url_allow_hosts>-->
<!-- Host should be specified exactly as in URL. The name is checked before DNS resolution.
Example: "clickhouse.com", "clickhouse.com." and "www.clickhouse.com" are different hosts.
If port is explicitly specified in URL, the host:port is checked as a whole.
If host specified here without port, any port with this host allowed.
"clickhouse.com" -> "clickhouse.com:443", "clickhouse.com:80" etc. is allowed, but "clickhouse.com:80" -> only "clickhouse.com:80" is allowed.
If the host is specified as IP address, it is checked as specified in URL. Example: "[2a02:6b8:a::a]".
If there are redirects and support for redirects is enabled, every redirect (the Location field) is checked.
Host should be specified using the host xml tag:
<host>clickhouse.com</host>
-->
<!-- Regular expression can be specified. RE2 engine is used for regexps.
Regexps are not aligned: don't forget to add ^ and $. Also don't forget to escape dot (.) metacharacter
(forgetting to do so is a common source of error).
-->
<!--</remote_url_allow_hosts>-->
<!-- If element has 'incl' attribute, then for it's value will be used corresponding substitution from another file.
By default, path to file with substitutions is /etc/metrika.xml. It could be changed in config in 'include_from' element.
Values for substitutions are specified in /clickhouse/name_of_substitution elements in that file.
-->
<!-- ZooKeeper is used to store metadata about replicas, when using Replicated tables.
Optional. If you don't use replicated tables, you could omit that.
See https://clickhouse.com/docs/en/engines/table-engines/mergetree-family/replication/
-->
<!--
<zookeeper>
<node>
<host>example1</host>
<port>2181</port>
</node>
<node>
<host>example2</host>
<port>2181</port>
</node>
<node>
<host>example3</host>
<port>2181</port>
</node>
</zookeeper>
-->
<!-- Substitutions for parameters of replicated tables.
Optional. If you don't use replicated tables, you could omit that.
See https://clickhouse.com/docs/en/engines/table-engines/mergetree-family/replication/#creating-replicated-tables
-->
<!--
<macros>
<shard>01</shard>
<replica>example01-01-1</replica>
</macros>
-->
<!-- Reloading interval for embedded dictionaries, in seconds. Default: 3600. -->
<builtin_dictionaries_reload_interval>3600</builtin_dictionaries_reload_interval>
<!-- Maximum session timeout, in seconds. Default: 3600. -->
<max_session_timeout>3600</max_session_timeout>
<!-- Default session timeout, in seconds. Default: 60. -->
<default_session_timeout>60</default_session_timeout>
<!-- Sending data to Graphite for monitoring. Several sections can be defined. -->
<!--
interval - send every X second
root_path - prefix for keys
hostname_in_path - append hostname to root_path (default = true)
metrics - send data from table system.metrics
events - send data from table system.events
asynchronous_metrics - send data from table system.asynchronous_metrics
-->
<!--
<graphite>
<host>localhost</host>
<port>42000</port>
<timeout>0.1</timeout>
<interval>60</interval>
<root_path>one_min</root_path>
<hostname_in_path>true</hostname_in_path>
<metrics>true</metrics>
<events>true</events>
<events_cumulative>false</events_cumulative>
<asynchronous_metrics>true</asynchronous_metrics>
</graphite>
<graphite>
<host>localhost</host>
<port>42000</port>
<timeout>0.1</timeout>
<interval>1</interval>
<root_path>one_sec</root_path>
<metrics>true</metrics>
<events>true</events>
<events_cumulative>false</events_cumulative>
<asynchronous_metrics>false</asynchronous_metrics>
</graphite>
-->
<!-- Serve endpoint for Prometheus monitoring. -->
<!--
endpoint - mertics path (relative to root, statring with "/")
port - port to setup server. If not defined or 0 than http_port used
metrics - send data from table system.metrics
events - send data from table system.events
asynchronous_metrics - send data from table system.asynchronous_metrics
status_info - send data from different component from CH, ex: Dictionaries status
-->
<!--
<prometheus>
<endpoint>/metrics</endpoint>
<port>9363</port>
<metrics>true</metrics>
<events>true</events>
<asynchronous_metrics>true</asynchronous_metrics>
<status_info>true</status_info>
</prometheus>
-->
<!-- Query log. Used only for queries with setting log_queries = 1. -->
<query_log>
<!-- What table to insert data. If table is not exist, it will be created.
When query log structure is changed after system update,
then old table will be renamed and new table will be created automatically.
-->
<database>system</database>
<table>query_log</table>
<!--
PARTITION BY expr: https://clickhouse.com/docs/en/table_engines/mergetree-family/custom_partitioning_key/
Example:
event_date
toMonday(event_date)
toYYYYMM(event_date)
toStartOfHour(event_time)
-->
<partition_by>toYYYYMM(event_date)</partition_by>
<!--
Table TTL specification: https://clickhouse.com/docs/en/engines/table-engines/mergetree-family/mergetree/#mergetree-table-ttl
Example:
event_date + INTERVAL 1 WEEK
event_date + INTERVAL 7 DAY DELETE
event_date + INTERVAL 2 WEEK TO DISK 'bbb'
<ttl>event_date + INTERVAL 30 DAY DELETE</ttl>
-->
<!-- Instead of partition_by, you can provide full engine expression (starting with ENGINE = ) with parameters,
Example: <engine>ENGINE = MergeTree PARTITION BY toYYYYMM(event_date) ORDER BY (event_date, event_time) SETTINGS index_granularity = 1024</engine>
-->
<!-- Interval of flushing data. -->
<flush_interval_milliseconds>7500</flush_interval_milliseconds>
</query_log>
<!-- Trace log. Stores stack traces collected by query profilers.
See query_profiler_real_time_period_ns and query_profiler_cpu_time_period_ns settings. -->
<trace_log>
<database>system</database>
<table>trace_log</table>
<partition_by>toYYYYMM(event_date)</partition_by>
<flush_interval_milliseconds>7500</flush_interval_milliseconds>
</trace_log>
<!-- Query thread log. Has information about all threads participated in query execution.
Used only for queries with setting log_query_threads = 1. -->
<query_thread_log>
<database>system</database>
<table>query_thread_log</table>
<partition_by>toYYYYMM(event_date)</partition_by>
<flush_interval_milliseconds>7500</flush_interval_milliseconds>
</query_thread_log>
<!-- Query views log. Has information about all dependent views associated with a query.
Used only for queries with setting log_query_views = 1. -->
<query_views_log>
<database>system</database>
<table>query_views_log</table>
<partition_by>toYYYYMM(event_date)</partition_by>
<flush_interval_milliseconds>7500</flush_interval_milliseconds>
</query_views_log>
<!-- Uncomment if use part log.
Part log contains information about all actions with parts in MergeTree tables (creation, deletion, merges, downloads).-->
<part_log>
<database>system</database>
<table>part_log</table>
<partition_by>toYYYYMM(event_date)</partition_by>
<flush_interval_milliseconds>7500</flush_interval_milliseconds>
</part_log>
<!-- Uncomment to write text log into table.
Text log contains all information from usual server log but stores it in structured and efficient way.
The level of the messages that goes to the table can be limited (<level>), if not specified all messages will go to the table.
<text_log>
<database>system</database>
<table>text_log</table>
<flush_interval_milliseconds>7500</flush_interval_milliseconds>
<level></level>
</text_log>
-->
<!-- Metric log contains rows with current values of ProfileEvents, CurrentMetrics collected with "collect_interval_milliseconds" interval. -->
<metric_log>
<database>system</database>
<table>metric_log</table>
<flush_interval_milliseconds>7500</flush_interval_milliseconds>
<collect_interval_milliseconds>1000</collect_interval_milliseconds>
</metric_log>
<!--
Asynchronous metric log contains values of metrics from
system.asynchronous_metrics.
-->
<asynchronous_metric_log>
<database>system</database>
<table>asynchronous_metric_log</table>
<!--
Asynchronous metrics are updated once a minute, so there is
no need to flush more often.
-->
<flush_interval_milliseconds>7000</flush_interval_milliseconds>
</asynchronous_metric_log>
<!--
OpenTelemetry log contains OpenTelemetry trace spans.
-->
<opentelemetry_span_log>
<!--
The default table creation code is insufficient, this <engine> spec
is a workaround. There is no 'event_time' for this log, but two times,
start and finish. It is sorted by finish time, to avoid inserting
data too far away in the past (probably we can sometimes insert a span
that is seconds earlier than the last span in the table, due to a race
between several spans inserted in parallel). This gives the spans a
global order that we can use to e.g. retry insertion into some external
system.
-->
<engine>
engine MergeTree
partition by toYYYYMM(finish_date)
order by (finish_date, finish_time_us, trace_id)
</engine>
<database>system</database>
<table>opentelemetry_span_log</table>
<flush_interval_milliseconds>7500</flush_interval_milliseconds>
</opentelemetry_span_log>
<!-- Crash log. Stores stack traces for fatal errors.
This table is normally empty. -->
<crash_log>
<database>system</database>
<table>crash_log</table>
<partition_by />
<flush_interval_milliseconds>1000</flush_interval_milliseconds>
</crash_log>
<!-- Session log. Stores user log in (successful or not) and log out events.
Note: session log has known security issues and should not be used in production.
-->
<!-- <session_log>
<database>system</database>
<table>session_log</table>
<partition_by>toYYYYMM(event_date)</partition_by>
<flush_interval_milliseconds>7500</flush_interval_milliseconds>
</session_log> -->
<!-- Profiling on Processors level. -->
<processors_profile_log>
<database>system</database>
<table>processors_profile_log</table>
<partition_by>toYYYYMM(event_date)</partition_by>
<flush_interval_milliseconds>7500</flush_interval_milliseconds>
</processors_profile_log>
<!-- <top_level_domains_path>/data/clickhouse/top_level_domains/</top_level_domains_path> -->
<!-- Custom TLD lists.
Format: <name>/path/to/file</name>
Changes will not be applied w/o server restart.
Path to the list is under top_level_domains_path (see above).
-->
<top_level_domains_lists>
<!--
<public_suffix_list>/path/to/public_suffix_list.dat</public_suffix_list>
-->
</top_level_domains_lists>
<!-- Configuration of external dictionaries. See:
https://clickhouse.com/docs/en/sql-reference/dictionaries/external-dictionaries/external-dicts
-->
<dictionaries_config>*_dictionary.xml</dictionaries_config>
<!-- Configuration of user defined executable functions -->
<user_defined_executable_functions_config>*_function.xml</user_defined_executable_functions_config>
<!-- Uncomment if you want data to be compressed 30-100% better.
Don't do that if you just started using ClickHouse.
-->
<!--
<compression>
<!- - Set of variants. Checked in order. Last matching case wins. If nothing matches, lz4 will be used. - ->
<case>
<!- - Conditions. All must be satisfied. Some conditions may be omitted. - ->
<min_part_size>10000000000</min_part_size> <!- - Min part size in bytes. - ->
<min_part_size_ratio>0.01</min_part_size_ratio> <!- - Min size of part relative to whole table size. - ->
<!- - What compression method to use. - ->
<method>zstd</method>
</case>
</compression>
-->
<!-- Configuration of encryption. The server executes a command to
obtain an encryption key at startup if such a command is
defined, or encryption codecs will be disabled otherwise. The
command is executed through /bin/sh and is expected to write
a Base64-encoded key to the stdout. -->
<encryption_codecs>
<!-- aes_128_gcm_siv -->
<!-- Example of getting hex key from env -->
<!-- the code should use this key and throw an exception if its length is not 16 bytes -->
<!--key_hex from_env="..."></key_hex -->
<!-- Example of multiple hex keys. They can be imported from env or be written down in config-->
<!-- the code should use these keys and throw an exception if their length is not 16 bytes -->
<!-- key_hex id="0">...</key_hex -->
<!-- key_hex id="1" from_env=".."></key_hex -->
<!-- key_hex id="2">...</key_hex -->
<!-- current_key_id>2</current_key_id -->
<!-- Example of getting hex key from config -->
<!-- the code should use this key and throw an exception if its length is not 16 bytes -->
<!-- key>...</key -->
<!-- example of adding nonce -->
<!-- nonce>...</nonce -->
<!-- /aes_128_gcm_siv -->
</encryption_codecs>
<!-- Allow to execute distributed DDL queries (CREATE, DROP, ALTER, RENAME) on cluster.
Works only if ZooKeeper is enabled. Comment it if such functionality isn't required. -->
<distributed_ddl>
<!-- Path in ZooKeeper to queue with DDL queries -->
<path>/clickhouse/task_queue/ddl</path>
<!-- Settings from this profile will be used to execute DDL queries -->
<!-- <profile>default</profile> -->
<!-- Controls how much ON CLUSTER queries can be run simultaneously. -->
<!-- <pool_size>1</pool_size> -->
<!--
Cleanup settings (active tasks will not be removed)
-->
<!-- Controls task TTL (default 1 week) -->
<!-- <task_max_lifetime>604800</task_max_lifetime> -->
<!-- Controls how often cleanup should be performed (in seconds) -->
<!-- <cleanup_delay_period>60</cleanup_delay_period> -->
<!-- Controls how many tasks could be in the queue -->
<!-- <max_tasks_in_queue>1000</max_tasks_in_queue> -->
</distributed_ddl>
<!-- Settings to fine tune MergeTree tables. See documentation in source code, in MergeTreeSettings.h -->
<!--
<merge_tree>
<max_suspicious_broken_parts>5</max_suspicious_broken_parts>
</merge_tree>
-->
<!-- Protection from accidental DROP.
If size of a MergeTree table is greater than max_table_size_to_drop (in bytes) than table could not be dropped with any DROP query.
If you want do delete one table and don't want to change clickhouse-server config, you could create special file <clickhouse-path>/flags/force_drop_table and make DROP once.
By default max_table_size_to_drop is 50GB; max_table_size_to_drop=0 allows to DROP any tables.
The same for max_partition_size_to_drop.
Uncomment to disable protection.
-->
<!-- <max_table_size_to_drop>0</max_table_size_to_drop> -->
<!-- <max_partition_size_to_drop>0</max_partition_size_to_drop> -->
<!-- Example of parameters for GraphiteMergeTree table engine -->
<graphite_rollup_example>
<pattern>
<regexp>click_cost</regexp>
<function>any</function>
<retention>
<age>0</age>
<precision>3600</precision>
</retention>
<retention>
<age>86400</age>
<precision>60</precision>
</retention>
</pattern>
<default>
<function>max</function>
<retention>
<age>0</age>
<precision>60</precision>
</retention>
<retention>
<age>3600</age>
<precision>300</precision>
</retention>
<retention>
<age>86400</age>
<precision>3600</precision>
</retention>
</default>
</graphite_rollup_example>
<!-- Directory in <clickhouse-path> containing schema files for various input formats.
The directory will be created if it doesn't exist.
-->
<format_schema_path>/data/clickhouse/format_schemas/</format_schema_path>
<!-- Default query masking rules, matching lines would be replaced with something else in the logs
(both text logs and system.query_log).
name - name for the rule (optional)
regexp - RE2 compatible regular expression (mandatory)
replace - substitution string for sensitive data (optional, by default - six asterisks)
-->
<query_masking_rules>
<rule>
<name>hide encrypt/decrypt arguments</name>
<regexp>((?:aes_)?(?:encrypt|decrypt)(?:_mysql)?)\s*\(\s*(?:'(?:\\'|.)+'|.*?)\s*\)</regexp>
<!-- or more secure, but also more invasive:
(aes_\w+)\s*\(.*\)
-->
<replace>\1(???)</replace>
</rule>
</query_masking_rules>
<!-- Uncomment to use custom http handlers.
rules are checked from top to bottom, first match runs the handler
url - to match request URL, you can use 'regex:' prefix to use regex match(optional)
methods - to match request method, you can use commas to separate multiple method matches(optional)
headers - to match request headers, match each child element(child element name is header name), you can use 'regex:' prefix to use regex match(optional)
handler is request handler
type - supported types: static, dynamic_query_handler, predefined_query_handler
query - use with predefined_query_handler type, executes query when the handler is called
query_param_name - use with dynamic_query_handler type, extracts and executes the value corresponding to the <query_param_name> value in HTTP request params
status - use with static type, response status code
content_type - use with static type, response content-type
response_content - use with static type, Response content sent to client, when using the prefix 'file://' or 'config://', find the content from the file or configuration send to client.
<http_handlers>
<rule>
<url>/</url>
<methods>POST,GET</methods>
<headers><pragma>no-cache</pragma></headers>
<handler>
<type>dynamic_query_handler</type>
<query_param_name>query</query_param_name>
</handler>
</rule>
<rule>
<url>/predefined_query</url>
<methods>POST,GET</methods>
<handler>
<type>predefined_query_handler</type>
<query>SELECT * FROM system.settings</query>
</handler>
</rule>
<rule>
<handler>
<type>static</type>
<status>200</status>
<content_type>text/plain; charset=UTF-8</content_type>
<response_content>config://http_server_default_response</response_content>
</handler>
</rule>
</http_handlers>
-->
<send_crash_reports>
<!-- Changing <enabled> to true allows sending crash reports to -->
<!-- the ClickHouse core developers team via Sentry https://sentry.io -->
<!-- Doing so at least in pre-production environments is highly appreciated -->
<enabled>false</enabled>
<!-- Change <anonymize> to true if you don't feel comfortable attaching the server hostname to the crash report -->
<anonymize>false</anonymize>
<!-- Default endpoint should be changed to different Sentry DSN only if you have -->
<!-- some in-house engineers or hired consultants who're going to debug ClickHouse issues for you -->
<endpoint>https://6f33034cfe684dd7a3ab9875e57b1c8d@o388870.ingest.sentry.io/5226277</endpoint>
</send_crash_reports>
<!-- Uncomment to disable ClickHouse internal DNS caching. -->
<!-- <disable_internal_dns_cache>1</disable_internal_dns_cache> -->
<!-- You can also configure rocksdb like this: -->
<!--
<rocksdb>
<options>
<max_background_jobs>8</max_background_jobs>
</options>
<column_family_options>
<num_levels>2</num_levels>
</column_family_options>
<tables>
<table>
<name>TABLE</name>
<options>
<max_background_jobs>8</max_background_jobs>
</options>
<column_family_options>
<num_levels>2</num_levels>
</column_family_options>
</table>
</tables>
</rocksdb>
-->
<!-- Uncomment if enable merge tree metadata cache -->
<!--merge_tree_metadata_cache>
<lru_cache_size>268435456</lru_cache_size>
<continue_if_corrupted>true</continue_if_corrupted>
</merge_tree_metadata_cache-->
</clickhouse>
1. Create table schemas
The statement for creating table schemas must be modified for StoneDB and ClickHouse respectively. This is because the syntax for creating table schemas varies with the storage engine.
For information about the statements after the modification, see section "Create Table."
2. Initialize data
Generate test data
The test data used in these tests is generated by DBGEN, 100 GB in size.
Download BDGEN from the TPC official website and compile the downloaded file to obtain an executable file named dbgen.
./dbgen -s $scale -C $chunks -S $i -f
-s: the scale factor.
-C: the number of chunks.
-S: the sequence number of the chunk generated by the current command.
Import data
Directly import tables part, region, nation, customer, and supplier. For tables lineitem, orders, and partsupp, we recommend that you use a script such as split_file2db.sh to split them before the import. For more information, see section "Scripts used in the tests".
3. Generate the SQL queries
Run the following command to generate the initial SQL queries.
#!/usr/bin/bash
db_type=$1
for i in {1..22}
do
./qgen -d $i -s 100 >./$db_type/$db_type"$i".sql
done
The syntax varies with the storage engine. Therefore, the 22 queries need to be modified. To obtain the SQL queries after modification, see section "Query".
You can download the attachment to simulate a test:
q.zip
4. Execute the script for stress testing
Before the test, the databases are restarted to clear cached data. Each test value is the average value of results obtained from three rounds of test.
Execute the script for stress testing:
#!/bin/bash
# systemctl start clickhouse-server
for (( i=1;i<=3;i=i+1 ))
do
./tpch_benchmark.sh
sleep 300
done
# systemctl stop clickhouse-server
#!/bin/bash
# stone
# host=
# port=
# user=
# password=
# database=
# ClickHouse
host=
port=
database=
# The absolate path. The following is for reference only.
banchdir=/path/tpc-h/queries
# db_type=ck #ck、stone、mysql
db_type=ck #ck、stone、mysql
resfile=$banchdir/$db_type/"TPCH_${db_type}_`date "+%Y%m%d%H%M%S"`"
#igqure=(1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22)
# Q9, Q16, Q19, and Q22 are skipped on ClickHouse, because the execution time is too long.
igqure=(9 16 19 22)
echo "start test run at"`date "+%Y-%m-%d %H:%M:%S"`|tee -a ${resfile}.out
echo "Path to log: ${resfile}"
for (( i=1; i<=22;i=i+1 ))
do
for j in ${igqure[@]}
do
if [[ $i -eq $j ]];then
echo "pass query$i.sql"
continue 2
fi
done
# if (( $i==13 || $i==15 ));then
# continue
# fi
queryfile=${db_type}${i}".sql"
echo "run query ${i}"|tee -a ${resfile}.out
# Use this for ClickHouse.
echo " $database $banchdir/query$i.sql " #|tee -a ${resfile}.out
start_time=`date "+%s.%N"`
clickhouse-client -h $host --port $port -d $database < $banchdir/query$i.sql |tee -a ${resfile}.out
# Use this for MySQL and StoneDB.
# mysql -u$user -p$password -h$host -P$port $database -e "source $banchdir/query$i.sql" 2>&1 |tee -a ${resfile}.out
# mysql -u$user -p$password -h$host -P$port $database -e "source $banchdir/query$i.sql" 2>&1 |tee -a ${resfile}.out
end_time=`date "+%s.%N"`
start_s=${start_time%.*}
start_nanos=${start_time#*.}
end_s=${end_time%.*}
end_nanos=${end_time#*.}
if [ "$end_nanos" -lt "$start_nanos" ];then
end_s=$(( 10#$end_s -1 ))
end_nanos=$(( 10#$end_nanos + 10 ** 9))
fi
time=$(( 10#$end_s - 10#$start_s )).`printf "%03d\n" $(( (10#$end_nanos - 10#$start_nanos)/10**6 ))`
echo ${queryfile} "the $i run cost "${time}" second start at "`date -d @$start_time "+%Y-%m-%d %H:%M:%S"`" stop at "`date -d @$end_time "+%Y-%m-%d %H:%M:%S"` >> ${resfile}.time
# systemctl stop clickhouse-server
done
Execute the script:
nohup ./start_benchmark.sh &
Space usage
- For StoneDB, 59 GB disk space is used.
- For ClickHouse, 42 GB disk space is used.
Test method
- In the tests, the TPC-H scripts are used to execute the TPC-H datasets in sequence.
- The test is performed for three times and the average values of the test results are used for performance comparison between StoneDB and ClickHouse.
Test scheme
- Deploy StoneDB on the server.
- Download ClickHouse and deploy it on a server that has the same configuration as the server on which StoneDB is deployed.
- Download and debug TPC-H and use DBGEN to generate 100 GB test data.
- Optimize the executable SQL scripts for creating and executing SQL queries.
- Perform the following steps respectively on ClickHouse and StoneDB:
- Connect to the database and execute the statement for creating table schemas.
- Import 100 GB test data.
- On the database, execute the 22 SQL queries for three times, and calculate the average value of each metric.
Compare the performance data between ClickHouse and StoneDB.
- Analyze the performance difference between ClickHouse and StoneDB.
- Write the test report and submit it for review. After the test report passes the review, the test is completed.
OS resource usage comparison
StoneDB provides better performance than ClickHouse, when comparing OS resource overhead, such as disk I/O, CPU utilization, system load, and IOPS.
CPU
StoneDB
ClickHouse
Disk IOPS
StoneDB
ClickHouse
Memory
StoneDB
ClickHouse
System Load
StoneDB
ClickHouse
Scripts used in the tests
CREATE TABLE
ClickHouse
create table nation ( n_nationkey bigint,
n_name char(25) ,
n_regionkey bigint,
n_comment varchar(152))engine=MergeTree order by (n_name,n_regionkey);
create table region ( r_regionkey bigint,
r_name char(25) ,
r_comment varchar(152))engine=MergeTree order by (r_name);
create table part ( p_partkey bigint,
p_name varchar(55) ,
p_mfgr char(25) ,
p_brand char(10) ,
p_type varchar(25) ,
p_size bigint,
p_container char(10) ,
p_retailprice decimal(15,2) ,
p_comment varchar(23) )engine=MergeTree order by (p_name,p_mfgr);
create table supplier ( s_suppkey bigint,
s_name char(25) ,
s_address varchar(40) ,
s_nationkey bigint,
s_phone char(15) ,
s_acctbal decimal(15,2) ,
s_comment varchar(101) )engine=MergeTree order by (s_suppkey,s_name);
create table partsupp ( ps_partkey bigint,
ps_suppkey bigint,
ps_availqty bigint,
ps_supplycost decimal(15,2) ,
ps_comment varchar(199) )engine=MergeTree order by (ps_partkey,ps_suppkey);
create table customer ( c_custkey bigint,
c_name varchar(25) ,
c_address varchar(40) ,
c_nationkey bigint,
c_phone char(15) ,
c_acctbal decimal(15,2) ,
c_mktsegment char(10) ,
c_comment varchar(117) )engine=MergeTree order by (c_custkey,c_name);
create table orders ( o_orderkey bigint,
o_custkey bigint,
o_orderstatus char(1) ,
o_totalprice decimal(15,2) ,
o_orderdate date ,
o_orderpriority char(15) ,
o_clerk char(15) ,
o_shippriority bigint,
o_comment varchar(79) )engine=MergeTree order by (o_orderkey,o_custkey);
create table lineitem ( l_orderkey bigint,
l_partkey bigint,
l_suppkey bigint,
l_linenumber bigint,
l_quantity decimal(15,2) ,
l_extendedprice decimal(15,2) ,
l_discount decimal(15,2) ,
l_tax decimal(15,2) ,
l_returnflag char(1) ,
l_linestatus char(1) ,
l_shipdate date ,
l_commitdate date ,
l_receiptdate date ,
l_shipinstruct char(25) ,
l_shipmode char(10) ,
l_comment varchar(44) )engine=MergeTree order by (l_shipdate,l_returnflag,l_linestatus);
StoneDB
create table nation ( n_nationkey integer not null,
n_name char(25) not null,
n_regionkey integer not null,
n_comment varchar(152),primary key (n_nationkey))engine=STONEDB;
create table region ( r_regionkey integer not null,
r_name char(25) not null,
r_comment varchar(152),primary key (r_regionkey))engine=STONEDB;
create table part ( p_partkey integer not null,
p_name varchar(55) not null,
p_mfgr char(25) not null,
p_brand char(10) not null,
p_type varchar(25) not null,
p_size integer not null,
p_container char(10) not null,
p_retailprice decimal(15,2) not null,
p_comment varchar(23) not null,primary key (p_partkey) )engine=STONEDB;
create table supplier ( s_suppkey integer not null,
s_name char(25) not null,
s_address varchar(40) not null,
s_nationkey integer not null,
s_phone char(15) not null,
s_acctbal decimal(15,2) not null,
s_comment varchar(101) not null,primary key (s_suppkey))engine=STONEDB;
create table partsupp ( ps_partkey integer not null,
ps_suppkey integer not null,
ps_availqty integer not null,
ps_supplycost decimal(15,2) not null,
ps_comment varchar(199) not null,primary key (ps_partkey,ps_suppkey) )engine=STONEDB;
create table customer ( c_custkey integer not null,
c_name varchar(25) not null,
c_address varchar(40) not null,
c_nationkey integer not null,
c_phone char(15) not null,
c_acctbal decimal(15,2) not null,
c_mktsegment char(10) not null,
c_comment varchar(117) not null,primary key (c_custkey))engine=STONEDB;
create table orders ( o_orderkey integer not null,
o_custkey integer not null,
o_orderstatus char(1) not null,
o_totalprice decimal(15,2) not null,
o_orderdate date not null,
o_orderpriority char(15) not null,
o_clerk char(15) not null,
o_shippriority integer not null,
o_comment varchar(79) not null,primary key (o_orderkey))engine=STONEDB;
create table lineitem ( l_orderkey integer not null,
l_partkey integer not null,
l_suppkey integer not null,
l_linenumber integer not null,
l_quantity decimal(15,2) not null,
l_extendedprice decimal(15,2) not null,
l_discount decimal(15,2) not null,
l_tax decimal(15,2) not null,
l_returnflag char(1) not null,
l_linestatus char(1) not null,
l_shipdate date not null,
l_commitdate date not null,
l_receiptdate date not null,
l_shipinstruct char(25) not null,
l_shipmode char(10) not null,
l_comment varchar(44) not null,primary key (l_orderkey,l_linenumber))engine=STONEDB;
Queries
SQL 1
select
l_returnflag,
l_linestatus,
sum(l_quantity) as sum_qty,
sum(l_extendedprice) as sum_base_price,
sum(l_extendedprice * (1 - l_discount)) as sum_disc_price,
sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) as sum_charge,
avg(l_quantity) as avg_qty,
avg(l_extendedprice) as avg_price,
avg(l_discount) as avg_disc,
count(*) as count_order
from
lineitem
where
-- l_shipdate <= date '1998-12-01' - interval '90' day (3)
l_shipdate <= date '1998-12-01' - interval '90' day
group by
l_returnflag,
l_linestatus
order by
l_returnflag,
l_linestatus;
SQL 2
select
s_acctbal,
s_name,
n_name,
p_partkey,
p_mfgr,
s_address,
s_phone,
s_comment
from
part,
supplier,
partsupp,
nation,
region
where
p_partkey = ps_partkey
and s_suppkey = ps_suppkey
and p_size = 15
and p_type like '%BRASS'
and s_nationkey = n_nationkey
and n_regionkey = r_regionkey
and r_name = 'EUROPE'
and ps_supplycost = (
select
min(ps_supplycost)
from
partsupp,
supplier,
nation,
region,
part
where
p_partkey = ps_partkey
and s_suppkey = ps_suppkey
and s_nationkey = n_nationkey
and n_regionkey = r_regionkey
and r_name = 'EUROPE'
)
order by
s_acctbal desc,
n_name,
s_name,
p_partkey
limit 100;
SQL 3
select
l_orderkey,
sum(l_extendedprice * (1 - l_discount)) as revenue,
o_orderdate,
o_shippriority
from
customer,
orders,
lineitem
where
c_mktsegment = 'BUILDING'
and c_custkey = o_custkey
and l_orderkey = o_orderkey
and o_orderdate < date '1995-03-15'
and l_shipdate > date '1995-03-15'
group by
l_orderkey,
o_orderdate,
o_shippriority
order by
revenue desc,
o_orderdate
limit 10;
SQL 4
select
o_orderpriority,
count(*) as order_count
from
orders,lineitem
where
l_orderkey = o_orderkey
and o_orderdate >= date '1993-07-01'
and o_orderdate < date '1993-07-01' + interval '3' month
and l_commitdate < l_receiptdate
and o_orderkey <> l_orderkey
group by
o_orderpriority
order by
o_orderpriority;
SQL 5
-- using default substitutions
select
n_name,
sum(l_extendedprice * (1 - l_discount)) as revenue
from
customer,
orders,
lineitem,
supplier,
nation,
region
where
c_custkey = o_custkey
and l_orderkey = o_orderkey
and l_suppkey = s_suppkey
and c_nationkey = s_nationkey
and s_nationkey = n_nationkey
and n_regionkey = r_regionkey
and r_name = 'ASIA'
and o_orderdate >= date '1994-01-01'
and o_orderdate < date '1994-01-01' + interval '1' year
group by
n_name
order by
revenue desc;
SQL 6
-- using default substitutions
select
sum(l_extendedprice * l_discount) as revenue
from
lineitem
where
l_shipdate >= date '1994-01-01'
and l_shipdate < date '1994-01-01' + interval '1' year
and l_discount between 0.06 - 0.01 and 0.06 + 0.01
and l_quantity < 24;
SQL 7
-- using default substitutions
select
supp_nation,
cust_nation,
l_year,
sum(volume) as revenue
from
(
select
n1.n_name as supp_nation,
n2.n_name as cust_nation,
extract(year from l_shipdate) as l_year,
l_extendedprice * (1 - l_discount) as volume
from
supplier,
lineitem,
orders,
customer,
nation n1,
nation n2
where
s_suppkey = l_suppkey
and o_orderkey = l_orderkey
and c_custkey = o_custkey
and s_nationkey = n1.n_nationkey
and c_nationkey = n2.n_nationkey
and (
(n1.n_name = 'FRANCE' and n2.n_name = 'GERMANY')
or (n1.n_name = 'GERMANY' and n2.n_name = 'FRANCE')
)
and l_shipdate between date '1995-01-01' and date '1996-12-31'
) as shipping
group by
supp_nation,
cust_nation,
l_year
order by
supp_nation,
cust_nation,
l_year;
SQL 8
-- using default substitutions
select
o_year,
sum(case
when nation = 'BRAZIL' then volume
else 0
end) / sum(volume) as mkt_share
from
(
select
extract(year from o_orderdate) as o_year,
l_extendedprice * (1 - l_discount) as volume,
n2.n_name as nation
from
part,
supplier,
lineitem,
orders,
customer,
nation n1,
nation n2,
region
where
p_partkey = l_partkey
and s_suppkey = l_suppkey
and l_orderkey = o_orderkey
and o_custkey = c_custkey
and c_nationkey = n1.n_nationkey
and n1.n_regionkey = r_regionkey
and r_name = 'AMERICA'
and s_nationkey = n2.n_nationkey
and o_orderdate between date '1995-01-01' and date '1996-12-31'
and p_type = 'ECONOMY ANODIZED STEEL'
) as all_nations
group by
o_year
order by
o_year;
SQL 9
-- using default substitutions
select
nation,
o_year,
sum(amount) as sum_profit
from
(
select
n_name as nation,
extract(year from o_orderdate) as o_year,
l_extendedprice * (1 - l_discount) - ps_supplycost * l_quantity as amount
from
part,
supplier,
lineitem,
partsupp,
orders,
nation
where
s_suppkey = l_suppkey
and ps_suppkey = l_suppkey
and ps_partkey = l_partkey
and p_partkey = l_partkey
and o_orderkey = l_orderkey
and s_nationkey = n_nationkey
and p_name like '%green%'
) as profit
group by
nation,
o_year
order by
nation,
o_year desc;
SQL 10
-- using default substitutions
select
c_custkey,
c_name,
sum(l_extendedprice * (1 - l_discount)) as revenue,
c_acctbal,
n_name,
c_address,
c_phone,
c_comment
from
customer,
orders,
lineitem,
nation
where
c_custkey = o_custkey
and l_orderkey = o_orderkey
and o_orderdate >= date '1993-10-01'
and o_orderdate < date '1993-10-01' + interval '3' month
and l_returnflag = 'R'
and c_nationkey = n_nationkey
group by
c_custkey,
c_name,
c_acctbal,
c_phone,
n_name,
c_address,
c_comment
order by
revenue desc
limit 20;
SQL 11
-- using default substitutions
select
ps_partkey,
sum(ps_supplycost * ps_availqty) as value
from
partsupp,
supplier,
nation
where
ps_suppkey = s_suppkey
and s_nationkey = n_nationkey
and n_name = 'GERMANY'
group by
ps_partkey having
sum(ps_supplycost * ps_availqty) > (
select
sum(ps_supplycost * ps_availqty) * 0.0000010000
from
partsupp,
supplier,
nation
where
ps_suppkey = s_suppkey
and s_nationkey = n_nationkey
and n_name = 'GERMANY'
)
order by
value desc;
SQL 12
-- using default substitutions
select
l_shipmode,
sum(case
when o_orderpriority = '1-URGENT'
or o_orderpriority = '2-HIGH'
then 1
else 0
end) as high_line_count,
sum(case
when o_orderpriority <> '1-URGENT'
and o_orderpriority <> '2-HIGH'
then 1
else 0
end) as low_line_count
from
orders,
lineitem
where
o_orderkey = l_orderkey
and l_shipmode in ('MAIL', 'SHIP')
and l_commitdate < l_receiptdate
and l_shipdate < l_commitdate
and l_receiptdate >= date '1994-01-01'
and l_receiptdate < date '1994-01-01' + interval '1' year
group by
l_shipmode
order by
l_shipmode;
SQL 13
-- using default substitutions
select
c_count,
count(*) as custdist
from
(
select
c_custkey as c_custkey,
count(o_orderkey) as c_count
from
customer left outer join orders on
c_custkey = o_custkey
and o_comment not like '%special%requests%'
group by
c_custkey
) as c_orders
group by
c_count
order by
custdist desc,
c_count desc;
SQL 14
-- using default substitutions
select
100.00 * sum(case
when p_type like 'PROMO%'
then l_extendedprice * (1 - l_discount)
else 0
end) / sum(l_extendedprice * (1 - l_discount)) as promo_revenue
from
lineitem,
part
where
l_partkey = p_partkey
and l_shipdate >= date '1995-09-01'
and l_shipdate < date '1995-09-01' + interval '1' month;
SQL 15
-- using default substitutions
-- For ClickHouse, views must be created in advance. Otherwise, error "failed at position 518 (end of query) (line 23, col 11)" is reported.
-- CREATE VIEW revenue0 AS SELECT l_suppkey AS supplier_no, sum(l_extendedprice * (1 - l_discount)) AS total_revenue FROM lineitem WHERE l_shipdate >= DATE '1996-01-01' AND l_shipdate < DATE '1996-04-01' GROUP BY l_suppkey;
select
s_suppkey,
s_name,
s_address,
s_phone,
total_revenue
from
supplier,
revenue0
where
s_suppkey = supplier_no
and total_revenue = (
select
max(total_revenue)
from
revenue0
)
order by
s_suppkey;
SQL 16
-- using default substitutions
select
p_brand,
p_type,
p_size,
count(distinct ps_suppkey) as supplier_cnt
from
partsupp,
part,supplier
where
p_partkey = ps_partkey
and p_brand <> 'Brand#45'
and p_type not like 'MEDIUM POLISHED%'
and p_size in (49, 14, 23, 45, 19, 3, 36, 9)
and ps_suppkey <> s_suppkey
and s_comment like '%Customer%Complaints%'
group by
p_brand,
p_type,
p_size
order by
supplier_cnt desc,
p_brand,
p_type,
p_size;
SQL 17
-- using default substitutions
select
sum(l_extendedprice) / 7.0 as avg_yearly
from
lineitem,
part
where
p_partkey = l_partkey
and p_brand = 'Brand#23'
and p_container = 'MED BOX'
and l_quantity < (
select
0.2 * avg(l_quantity)
from
lineitem,part
where
l_partkey = p_partkey
);
SQL 18
-- using default substitutions
select
c_name,
c_custkey,
o_orderkey,
o_orderdate,
o_totalprice,
sum(l_quantity)
from
customer,
orders,
lineitem
where
o_orderkey =l_orderkey
and c_custkey = o_custkey
and o_orderkey = l_orderkey
group by
c_name,
c_custkey,
o_orderkey,
o_orderdate,
o_totalprice,
l_orderkey
having sum(l_quantity) > 300
order by
o_totalprice desc,
o_orderdate
limit 100;
SQL 19
-- using default substitutions
select
sum(l_extendedprice* (1 - l_discount)) as revenue
from
lineitem,
part
where
(
p_partkey = l_partkey
and p_brand = 'Brand#12'
and p_container in ('SM CASE', 'SM BOX', 'SM PACK', 'SM PKG')
and l_quantity >= 1 and l_quantity <= 1 + 10
and p_size between 1 and 5
and l_shipmode in ('AIR', 'AIR REG')
and l_shipinstruct = 'DELIVER IN PERSON'
)
or
(
p_partkey = l_partkey
and p_brand = 'Brand#23'
and p_container in ('MED BAG', 'MED BOX', 'MED PKG', 'MED PACK')
and l_quantity >= 10 and l_quantity <= 10 + 10
and p_size between 1 and 10
and l_shipmode in ('AIR', 'AIR REG')
and l_shipinstruct = 'DELIVER IN PERSON'
)
or
(
p_partkey = l_partkey
and p_brand = 'Brand#34'
and p_container in ('LG CASE', 'LG BOX', 'LG PACK', 'LG PKG')
and l_quantity >= 20 and l_quantity <= 20 + 10
and p_size between 1 and 15
and l_shipmode in ('AIR', 'AIR REG')
and l_shipinstruct = 'DELIVER IN PERSON'
) limit 1;
SQL 20
-- using default substitutions
select
s_name,
s_address
from
supplier,
nation
where
s_suppkey in (
select
ps_suppkey
from
partsupp
where
ps_partkey in (
select
p_partkey
from
part
where
p_name like 'forest%'
)
and ps_availqty > (
select
0.5 * sum(l_quantity)
from
lineitem,partsupp
where
l_partkey = ps_partkey
and l_suppkey = ps_suppkey
and l_shipdate >= date '1994-01-01'
and l_shipdate < date '1994-01-01' + interval '1' year
)
)
and s_nationkey = n_nationkey
and n_name = 'CANADA'
order by
s_name;
SQL 21
-- using default substitutions
select
s_name,
count(*) as numwait
from
supplier,
lineitem l1,
orders,
nation,lineitem l2,lineitem l3
where
s_suppkey = l1.l_suppkey
and o_orderkey = l1.l_orderkey
and o_orderstatus = 'F'
and l1.l_receiptdate > l1.l_commitdate
and l1.l_orderkey=l2.l_orderkey
and l2.l_orderkey = l1.l_orderkey
and l2.l_suppkey <> l1.l_suppkey
and l1.l_orderkey<> l3.l_orderkey
AND l3.l_orderkey = l1.l_orderkey
and l3.l_suppkey <> l1.l_suppkey
and l3.l_receiptdate > l3.l_commitdate
and s_nationkey = n_nationkey
and n_name = 'SAUDI ARABIA'
group by
s_name
order by
numwait desc,
s_name
limit 100;
SQL 22
select
cntrycode,
count(*) as numcust,
sum(c_acctbal) as totacctbal
from
(
select
substring(c_phone from 1 for 2) as cntrycode,
c_acctbal
from
customer,orders
where
substring(c_phone from 1 for 2) in
('13', '31', '23', '29', '30', '18', '17')
and c_acctbal > (
select
avg(c_acctbal)
from
customer
where
c_acctbal > 0.00
and substring(c_phone from 1 for 2) in
('13', '31', '23', '29', '30', '18', '17')
)
and o_custkey = c_custkey
and c_custkey <> o_custkey
) as custsale
group by
cntrycode
order by
cntrycode;