ClickHouse/docs/en/engines/table-engines/integrations/s3queue.md

slug	sidebar_position	sidebar_label
/en/engines/table-engines/integrations/s3queue	181	S3Queue

[experimental] 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.

:::note This table engine is experimental. To use it, set allow_experimental_s3queue to 1 by using the SET command:

SET allow_experimental_s3queue=1

:::

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} where N, 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: unordered.

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.

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:

1. Use the engine to create a table for consuming from specified path in S3 and consider it a data stream.
2. Create a table with the desired structure.
3. 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',
        keeper_path = '/clickhouse/s3queue/';

  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.

:::note If the listing of files contains number ranges with leading zeros, use the construction with braces for each digit separately or use ?. :::

Introspection

For introspection use system.s3queue stateless table and system.s3queue_log persistent table.

1. system.s3queue. This table is not persistent and shows in-memory state of S3Queue: 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 'SYSTEM TABLE is built on the fly.' │
└────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘

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:

2. system.s3queue_log. Persistent table. Has the same information as system.s3queue, but for processed and failed 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: