S3Queue Table Engine
This engine provides integration with Amazon S3 ecosystem and allows streaming import. This engine is similar to the Kafka, RabbitMQ engines, but provides S3-specific features.
Create Table
CREATE TABLE s3_queue_engine_table (name String, value UInt32)
ENGINE = S3Queue(path, [NOSIGN, | aws_access_key_id, aws_secret_access_key,] format, [compression])
[SETTINGS]
[mode = 'unordered',]
[after_processing = 'keep',]
[keeper_path = '',]
[s3queue_loading_retries = 0,]
[s3queue_processing_threads_num = 1,]
[s3queue_enable_logging_to_s3queue_log = 0,]
[s3queue_polling_min_timeout_ms = 1000,]
[s3queue_polling_max_timeout_ms = 10000,]
[s3queue_polling_backoff_ms = 0,]
[s3queue_tracked_file_ttl_sec = 0,]
[s3queue_tracked_files_limit = 1000,]
[s3queue_cleanup_interval_min_ms = 10000,]
[s3queue_cleanup_interval_max_ms = 30000,]
Engine parameters
path
— Bucket url with path to file. Supports following wildcards in readonly mode:*
,**
,?
,{abc,def}
and{N..M}
whereN
,M
— numbers,'abc'
,'def'
— strings. For more information see below.NOSIGN
- If this keyword is provided in place of credentials, all the requests will not be signed.format
— The format of the file.aws_access_key_id
,aws_secret_access_key
- Long-term credentials for the AWS account user. You can use these to authenticate your requests. Parameter is optional. If credentials are not specified, they are used from the configuration file. For more information see Using S3 for Data Storage.compression
— Compression type. Supported values:none
,gzip/gz
,brotli/br
,xz/LZMA
,zstd/zst
. Parameter is optional. By default, it will autodetect compression by file extension.
Example
CREATE TABLE s3queue_engine_table (name String, value UInt32)
ENGINE=S3Queue('https://clickhouse-public-datasets.s3.amazonaws.com/my-test-bucket-768/*', 'CSV', 'gzip')
SETTINGS
mode = 'unordered';
Using named collections:
<clickhouse>
<named_collections>
<s3queue_conf>
<url>'https://clickhouse-public-datasets.s3.amazonaws.com/my-test-bucket-768/*</url>
<access_key_id>test<access_key_id>
<secret_access_key>test</secret_access_key>
</s3queue_conf>
</named_collections>
</clickhouse>
CREATE TABLE s3queue_engine_table (name String, value UInt32)
ENGINE=S3Queue(s3queue_conf, format = 'CSV', compression_method = 'gzip')
SETTINGS
mode = 'ordered';
Settings
mode
Possible values:
- unordered — With unordered mode, the set of all already processed files is tracked with persistent nodes in ZooKeeper.
- ordered — With ordered mode, only the max name of the successfully consumed file, and the names of files that will be retried after unsuccessful loading attempt are being stored in ZooKeeper.
Default value: ordered
in versions before 24.6. Starting with 24.6 there is no default value, the setting becomes required to be specified manually. For tables created on earlier versions the default value will remain Ordered
for compatibility.
after_processing
Delete or keep file after successful processing. Possible values:
- keep.
- delete.
Default value: keep
.
keeper_path
The path in ZooKeeper can be specified as a table engine setting or default path can be formed from the global configuration-provided path and table UUID. Possible values:
- String.
Default value: /
.
s3queue_loading_retries
Retry file loading up to specified number of times. By default, there are no retries. Possible values:
- Positive integer.
Default value: 0
.
s3queue_processing_threads_num
Number of threads to perform processing. Applies only for Unordered
mode.
Default value: 1
.
s3queue_enable_logging_to_s3queue_log
Enable logging to system.s3queue_log
.
Default value: 0
.
s3queue_polling_min_timeout_ms
Minimal timeout before next polling (in milliseconds).
Possible values:
- Positive integer.
Default value: 1000
.
s3queue_polling_max_timeout_ms
Maximum timeout before next polling (in milliseconds).
Possible values:
- Positive integer.
Default value: 10000
.
s3queue_polling_backoff_ms
Polling backoff (in milliseconds).
Possible values:
- Positive integer.
Default value: 0
.
s3queue_tracked_files_limit
Allows to limit the number of Zookeeper nodes if the 'unordered' mode is used, does nothing for 'ordered' mode. If limit reached the oldest processed files will be deleted from ZooKeeper node and processed again.
Possible values:
- Positive integer.
Default value: 1000
.
s3queue_tracked_file_ttl_sec
Maximum number of seconds to store processed files in ZooKeeper node (store forever by default) for 'unordered' mode, does nothing for 'ordered' mode. After the specified number of seconds, the file will be re-imported.
Possible values:
- Positive integer.
Default value: 0
.
s3queue_cleanup_interval_min_ms
For 'Ordered' mode. Defines a minimum boundary for reschedule interval for a background task, which is responsible for maintaining tracked file TTL and maximum tracked files set.
Default value: 10000
.
s3queue_cleanup_interval_max_ms
For 'Ordered' mode. Defines a maximum boundary for reschedule interval for a background task, which is responsible for maintaining tracked file TTL and maximum tracked files set.
Default value: 30000
.
s3queue_buckets
For 'Ordered' mode. Available since 24.6
. If there are several replicas of S3Queue table, each working with the same metadata directory in keeper, the value of s3queue_buckets
needs to be equal to at least the number of replicas. If s3queue_processing_threads
setting is used as well, it makes sense to increase the value of s3queue_buckets
setting even further, as it defines the actual parallelism of S3Queue
processing.
S3-related Settings
Engine supports all s3 related settings. For more information about S3 settings see here.
Description
SELECT
is not particularly useful for streaming import (except for debugging), because each file can be imported only once. It is more practical to create real-time threads using materialized views. To do this:
- Use the engine to create a table for consuming from specified path in S3 and consider it a data stream.
- Create a table with the desired structure.
- Create a materialized view that converts data from the engine and puts it into a previously created table.
When the MATERIALIZED VIEW
joins the engine, it starts collecting data in the background.
Example:
CREATE TABLE s3queue_engine_table (name String, value UInt32)
ENGINE=S3Queue('https://clickhouse-public-datasets.s3.amazonaws.com/my-test-bucket-768/*', 'CSV', 'gzip')
SETTINGS
mode = 'unordered';
CREATE TABLE stats (name String, value UInt32)
ENGINE = MergeTree() ORDER BY name;
CREATE MATERIALIZED VIEW consumer TO stats
AS SELECT name, value FROM s3queue_engine_table;
SELECT * FROM stats ORDER BY name;
Virtual columns
_path
— Path to the file._file
— Name of the file.
For more information about virtual columns see here.
Wildcards In Path
path
argument can specify multiple files using bash-like wildcards. For being processed file should exist and match to the whole path pattern. Listing of files is determined during SELECT
(not at CREATE
moment).
*
— Substitutes any number of any characters except/
including empty string.**
— Substitutes any number of any characters include/
including empty string.?
— Substitutes any single character.{some_string,another_string,yet_another_one}
— Substitutes any of strings'some_string', 'another_string', 'yet_another_one'
.{N..M}
— Substitutes any number in range from N to M including both borders. N and M can have leading zeroes e.g.000..078
.
Constructions with {}
are similar to the remote table function.
Limitations
- Duplicated rows can be as a result of:
an exception happens during parsing in the middle of file processing and retries are enabled via
s3queue_loading_retries
;S3Queue
is configured on multiple servers pointing to the same path in zookeeper and keeper session expires before one server managed to commit processed file, which could lead to another server taking processing of the file, which could be partially or fully processed by the first server;abnormal server termination.
S3Queue
is configured on multiple servers pointing to the same path in zookeeper andOrdered
mode is used, thens3queue_loading_retries
will not work. This will be fixed soon.
Introspection
For introspection use system.s3queue
stateless table and system.s3queue_log
persistent table.
system.s3queue
. This table is not persistent and shows in-memory state ofS3Queue
: which files are currently being processed, which files are processed or failed.
┌─statement──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│ CREATE TABLE system.s3queue
(
`database` String,
`table` String,
`file_name` String,
`rows_processed` UInt64,
`status` String,
`processing_start_time` Nullable(DateTime),
`processing_end_time` Nullable(DateTime),
`ProfileEvents` Map(String, UInt64)
`exception` String
)
ENGINE = SystemS3Queue
COMMENT 'Contains in-memory state of S3Queue metadata and currently processed rows per file.' │
└────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
Example:
SELECT *
FROM system.s3queue
Row 1:
──────
zookeeper_path: /clickhouse/s3queue/25ea5621-ae8c-40c7-96d0-cec959c5ab88/3b3f66a1-9866-4c2e-ba78-b6bfa154207e
file_name: wikistat/original/pageviews-20150501-030000.gz
rows_processed: 5068534
status: Processed
processing_start_time: 2023-10-13 13:09:48
processing_end_time: 2023-10-13 13:10:31
ProfileEvents: {'ZooKeeperTransactions':3,'ZooKeeperGet':2,'ZooKeeperMulti':1,'SelectedRows':5068534,'SelectedBytes':198132283,'ContextLock':1,'S3QueueSetFileProcessingMicroseconds':2480,'S3QueueSetFileProcessedMicroseconds':9985,'S3QueuePullMicroseconds':273776,'LogTest':17}
exception:
system.s3queue_log
. Persistent table. Has the same information assystem.s3queue
, but forprocessed
andfailed
files.
The table has the following structure:
SHOW CREATE TABLE system.s3queue_log
Query id: 0ad619c3-0f2a-4ee4-8b40-c73d86e04314
┌─statement──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│ CREATE TABLE system.s3queue_log
(
`event_date` Date,
`event_time` DateTime,
`table_uuid` String,
`file_name` String,
`rows_processed` UInt64,
`status` Enum8('Processed' = 0, 'Failed' = 1),
`processing_start_time` Nullable(DateTime),
`processing_end_time` Nullable(DateTime),
`ProfileEvents` Map(String, UInt64),
`exception` String
)
ENGINE = MergeTree
PARTITION BY toYYYYMM(event_date)
ORDER BY (event_date, event_time)
SETTINGS index_granularity = 8192 │
└────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
In order to use system.s3queue_log
define its configuration in server config file:
<s3queue_log>
<database>system</database>
<table>s3queue_log</table>
</s3queue_log>
Example:
SELECT *
FROM system.s3queue_log
Row 1:
──────
event_date: 2023-10-13
event_time: 2023-10-13 13:10:12
table_uuid:
file_name: wikistat/original/pageviews-20150501-020000.gz
rows_processed: 5112621
status: Processed
processing_start_time: 2023-10-13 13:09:48
processing_end_time: 2023-10-13 13:10:12
ProfileEvents: {'ZooKeeperTransactions':3,'ZooKeeperGet':2,'ZooKeeperMulti':1,'SelectedRows':5112621,'SelectedBytes':198577687,'ContextLock':1,'S3QueueSetFileProcessingMicroseconds':1934,'S3QueueSetFileProcessedMicroseconds':17063,'S3QueuePullMicroseconds':5841972,'LogTest':17}
exception: