Blog

Navigating Databend's Configuration Maze: A Guide for Developers and Operators

PsiACEOct 18, 2023

Databend, a powerful data warehouse, offers a myriad of configuration options for its Query and Meta services. Understanding and managing these configurations can be overwhelming, especially when it comes to the various formats and syntaxes used in different environments. In this post, we'll demystify Databend's configuration landscape and provide a comprehensive guide to help developers and operators alike successfully navigate its complexities.

Configuration Basics

Before diving into the specifics of Query and Meta configurations, it's essential to understand the basics. Databend supports three configuration methods, each with its own priority and use case:

  1. Command-line options: Useful for temporary, local overrides of environment variables or configuration files.
  2. Environment variables: Ideal for Kubernetes and other cloud environments, allowing for flexible configuration changes without altering the configuration files.
  3. Configuration files: The recommended approach for most use cases, providing a structured and version-controlled way to manage configurations.

Configuration in Databend Query

Regardless of the configuration method used, the configuration options in Databend Query can be seen as a flattened tree-like mapping of code, following the logic of "configuration domain" + "configuration item."

  • In environment variables and configuration files, the code is flattened using serfig, with
    _
    used as a separator.
  • Command-line options differ slightly: they use
    -
    as a separator, and some command-line arguments do not have a bound configuration domain.

Example:
admin_api_address
Configuration

To better understand the mapping relationship, let's start with the

admin_api_address
configuration option. This setting determines the address and port that the admin API will listen on.

  • In a TOML configuration file, the setting is defined as follow. The

    query
    section represents the configuration domain, and the
    admin_api_address
    is the specific option within that domain.

    [query]
    ...
    # Databend Query http address. For admin RESET API.
    admin_api_address = "0.0.0.0:8080"
    ...
  • In environment variable, it is represented as

    QUERY_ADMIN_API_ADDRESS
    , where
    QUERY
    represents the configuration domain and
    ADMIN_API_ADDRESS
    is the specific configuration option. To set the admin API address using an environment variable, you can use the following command:

    export QUERY_ADMIN_API_ADDRESS=0.0.0.0:8080
  • Command-line option, however, do not follow the same naming convention as environment variable or configuration file. Instead, the configuration option is used. So, you can adjust this value using the

    --admin-api-address
    command line argument.

    databend-query --admin-api-address=0.0.0.0:8080

Note: In this case, command-line option is not bound to a specific configuration domain. However, if configuring

--storage-s3-access-key-id
, the configuration domain would be "storage" + "s3", and "access-key-id" would be the specific configuration option. You can use "databend-query --help" to view all supported command-line arguments.

Mapping Configuration Options to Code

Let's dive into the code related to configuration to further understand the mapping relationship (located in

src/query/config/src/config.rs
):

pub struct Config {
...
#[clap(flatten)]
pub query: QueryConfig,
...
}

/// Query config group.
#[derive(Clone, Debug, PartialEq, Eq, Serialize, Deserialize, Args)]
#[serde(default, deny_unknown_fields)]
pub struct QueryConfig {
...
#[clap(long, default_value = "127.0.0.1:8080")]
pub admin_api_address: String,
...
}

In the code, the top-level structure is

Config
, and
admin_api_address
is a configuration option within
pub query: QueryConfig
. After processing with
serfig
, it needs to be represented by either "QUERY" or "[query]" to indicate its configuration domain, while the configuration option remains as
admin_api_address
.

For command-line options, the specific option name and default value are controlled by

#[clap(long = "<long-name>", default_value = "<value>")]
. clap takes over the configuration:

  • admin_api_address
    becomes
    --admin-api-address
    .
  • For
    --storage-s3-access-key-id
    , the actual code hierarchy is
    Config -> StorageConfig -> S3StorageConfig -> access_key_id
    , annotated with
    #[clap(long = "storage-s3-access-key-id", default_value_t)]
    . Therefore, it needs to be configured with
    --storage-s3-access-key-id
    .

Configuration in Databend Meta

The Meta service's configuration follows a similar structure to the Query service, with command-line arguments and configuration files playing a similar form. However, environment variables are managed using custom one-to-one mappings (powered by

serde-env
in serfig), but can still be understood based on "configuration domain" + "configuration option".

Example:
log_dir
Configuration

Let's explore the mapping between the different configuration methods for the

log_dir
option:

  • In the configuration file, it applies globally and can be set as:

    log_dir = "./.databend/logs"
  • In environment variables, it needs to be set as

    METASRV_LOG_DIR
    , where
    METASRV
    represents the configuration domain, and "LOG_DIR" is the specific configuration option.

    expert METASRV_LOG_DIR=./.databend/logs
  • For command-line configuration, it can be set directly using

    --log-dir
    .

    databend-meta --log-dir=./.databend/logs

Mapping Configuration Options to Code

Now, let's deconstruct the mapping through the code (located in

src/meta/service/src/configs/outer_v0.rs
):

#[derive(Clone, Debug, Serialize, Deserialize, PartialEq, Eq, Parser)]
#[clap(about, version = &**METASRV_COMMIT_VERSION, author)]
#[serde(default)]
pub struct Config {
...
/// Log file dir
#[clap(long = "log-dir", default_value = "./.databend/logs")]
pub log_dir: String,
...
}

The configuration options related to configuration files and command-line options are managed by the

Config
structure, following the same logic as Databend Query.

For environment variables, the configuration options are processed by the

ConfigViaEnv
structure, which is generated by the macro
serde::Deserialize
, based on the
Config
structure.

/// #[serde(flatten)] doesn't work correctly for env.
/// We should work around it by flatten them manually.
/// We are seeking for better solutions.
#[derive(Clone, Debug, Serialize, Deserialize, PartialEq, Eq)]
#[serde(default)]
pub struct ConfigViaEnv {
...
pub metasrv_log_dir: String,
...
}

// Implement Into target on ConfigViaEnv to make the transform logic more clear.
#[allow(clippy::from_over_into)]
impl Into<Config> for ConfigViaEnv {
fn into(self) -> Config {
...
Config {
// cmd, key, value and prefix should only be passed in from CLI
...
log_dir: self.metasrv_log_dir,
...
}
}
}

Therefore,

metasrv_log_dir
corresponds to the environment variable
METASRV_LOG_DIR
, and ultimately maps to the
log_dir
option in
Config
, thus associating it with the configuration file and command line option
--log-dir
.

Implicit Environment Variables

While some environment variables is not a formal option listed in the configuration options, it can still be used as an environment variable for configuration purposes.

This is mainly due to the absence of setting corresponding configuration options, which triggers the rollback mechanism of reqsign. It reads some commonly used environment variables of the corresponding service to ensure its proper operation as much as possible.

The mapping and usage of these environment variables can be understood by examining the relevant code sections.

Example:
AWS_ACCESS_KEY_ID
Environment Variable

In the implementation, there is a check for the

STORAGE_S3_ACCESS_KEY_ID
configuration option, which aligns with the configuration and environment variable mapping.

However, if the corresponding configuration is not provided, a fallback mechanism is triggered.

reqsign
will check
AWS_S3_ACCESS_KEY_ID
to obtain possible value.

This is also the reason why commands like the one below can work correctly.

docker run \
-p 8000:8000 \
-p 3307:3307 \
-v meta_storage_dir:/var/lib/databend/meta \
-v query_storage_dir:/var/lib/databend/query \
-v log_dir:/var/log/databend \
-e QUERY_DEFAULT_USER=databend \
-e QUERY_DEFAULT_PASSWORD=databend \
-e QUERY_STORAGE_TYPE=s3 \
-e AWS_S3_ENDPOINT=http://172.17.0.2:9000 \
-e AWS_S3_BUCKET=databend \
-e AWS_ACCESS_KEY_ID=ROOTUSER \
-e AWS_SECRET_ACCESS_KEY=CHANGEME123 \
datafuselabs/databend

Mapping Implicit Environment Variables to Code

Let's examine the relevant code snippet in

src/common/storage/src/operator.rs
(line 244):

builder.access_key_id(&cfg.access_key_id);

The

access_key_id()
function in the default behavior of the opendal library handles the configuration:

/// Set access_key_id of this backend.
///
/// - If access_key_id is set, we will take user's input first.
/// - If not, we will try to load it from environment.
pub fn access_key_id(&mut self, v: &str) -> &mut Self {...}

Since

disable_config_load
is not explicitly set, the S3 accessor will attempt to load the configuration from the environment variables while building. The code snippet responsible for this behavior is found in
AwsConfig
in the
reqsign
library:

pub struct AwsConfig {
/// `access_key_id` will be loaded from:
/// - this field if it's `is_some`
/// - env value: `AWS_ACCESS_KEY_ID`
/// - profile config: `aws_access_key_id`
pub access_key_id: Option<String>,
...
}

So if

access_key_id
is not provided, the library will attempt to load it from the
AWS_ACCESS_KEY_ID
environment variable.

This also allows you to choose familiar AWS or other service examples' default environment variables when using Databend in practice.

Conclusion

Understanding configuration management in Databend is crucial for developers and operators to effectively manage and fine-tune the database server program. By leveraging command-line arguments, environment variables, and configuration files, users can tailor the configurations to meet their specific needs. The code examples and explanations provided in this blog post serve as a guide to navigating the configuration management in Databend Query and Databend Meta.

Share this post

Subscribe to our newsletter

Stay informed on feature releases, product roadmap, support, and cloud offerings!