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clickhouse-rs

Official pure Rust typed client for ClickHouse DB.

• Uses serde for encoding/decoding rows.
• Supports serde attributes: skip_serializing, skip_deserializing, rename.
• Uses RowBinary encoding over HTTP transport.
  • There are plans to switch to Native over TCP.
• Supports TLS (see native-tls and rustls-tls features below).
• Supports compression and decompression (LZ4 and LZ4HC).
• Provides API for selecting.
• Provides API for inserting.
• Provides API for infinite transactional (see below) inserting.
• Provides API for watching live views.
• Provides mocks for unit testing.

Note: ch2rs is useful to generate a row type from ClickHouse.

Usage

To use the crate, add this to your Cargo.toml:

[dependencies]
clickhouse = "0.13.1"

[dev-dependencies]
clickhouse = { version = "0.13.1", features = ["test-util"] }

Note about ClickHouse prior to v22.6

CH server older than v22.6 (2022-06-16) handles RowBinary incorrectly in some rare cases. Use 0.11 and enable wa-37420 feature to solve this problem. Don't use it for newer versions.

Create a client

use clickhouse::Client;

let client = Client::default()
    .with_url("http://localhost:8123")
    .with_user("name")
    .with_password("123")
    .with_database("test");

• Reuse created clients or clone them in order to reuse a connection pool.

Select rows

use serde::Deserialize;
use clickhouse::Row;

#[derive(Row, Deserialize)]
struct MyRow<'a> {
    no: u32,
    name: &'a str,
}

let mut cursor = client
    .query("SELECT ?fields FROM some WHERE no BETWEEN ? AND ?")
    .bind(500)
    .bind(504)
    .fetch::<MyRow<'_>>()?;

while let Some(row) = cursor.next().await? { .. }

• Placeholder ?fields is replaced with no, name (fields of Row).
• Placeholder ? is replaced with values in following bind() calls.
• Convenient fetch_one::<Row>() and fetch_all::<Row>() can be used to get a first row or all rows correspondingly.
• sql::Identifier can be used to bind table names.

Note that cursors can return an error even after producing some rows. To avoid this, use client.with_option("wait_end_of_query", "1") in order to enable buffering on the server-side. More details. The buffer_size option can be useful too.

Insert a batch

use serde::Serialize;
use clickhouse::Row;

#[derive(Row, Serialize)]
struct MyRow {
    no: u32,
    name: String,
}

let mut insert = client.insert("some")?;
insert.write(&MyRow { no: 0, name: "foo".into() }).await?;
insert.write(&MyRow { no: 1, name: "bar".into() }).await?;
insert.end().await?;

• If end() isn't called, the INSERT is aborted.
• Rows are being sent progressively to spread network load.
• ClickHouse inserts batches atomically only if all rows fit in the same partition and their number is less max_insert_block_size.

Infinite inserting

Requires the inserter feature.

let mut inserter = client.inserter("some")?
    .with_timeouts(Some(Duration::from_secs(5)), Some(Duration::from_secs(20)))
    .with_max_bytes(50_000_000)
    .with_max_rows(750_000)
    .with_period(Some(Duration::from_secs(15)));

inserter.write(&MyRow { no: 0, name: "foo".into() })?;
inserter.write(&MyRow { no: 1, name: "bar".into() })?;
let stats = inserter.commit().await?;
if stats.rows > 0 {
    println!(
        "{} bytes, {} rows, {} transactions have been inserted",
        stats.bytes, stats.rows, stats.transactions,
    );
}

• Inserter ends an active insert in commit() if thresholds (max_bytes, max_rows, period) are reached.
• The interval between ending active INSERTs can be biased by using with_period_bias to avoid load spikes by parallel inserters.
• Inserter::time_left() can be used to detect when the current period ends. Call Inserter::commit() again to check limits if your stream emits items rarely.
• Time thresholds implemented by using quanta crate to speed the inserter up. Not used if test-util is enabled (thus, time can be managed by tokio::time::advance() in custom tests).
• All rows between commit() calls are inserted in the same INSERT statement.
• Do not forget to flush if you want to terminate inserting:

inserter.end().await?;

Perform DDL

client.query("DROP TABLE IF EXISTS some").execute().await?;

Live views

Requires the watch feature.

let mut cursor = client
    .watch("SELECT max(no), argMax(name, no) FROM some")
    .fetch::<Row<'_>>()?;

let (version, row) = cursor.next().await?.unwrap();
println!("live view updated: version={}, row={:?}", version, row);

// Use `only_events()` to iterate over versions only.
let mut cursor = client.watch("some_live_view").limit(20).only_events().fetch()?;
println!("live view updated: version={:?}", cursor.next().await?);

• Use carefully.
• This code uses or creates if not exists a temporary live view named lv_{sha1(query)} to reuse the same live view by parallel watchers.
• You can specify a name instead of a query.
• This API uses JSONEachRowWithProgress under the hood because of the issue.
• Only struct rows can be used. Avoid fetch::<u64>() and other without specified names.

See examples.

Feature Flags

• lz4 (enabled by default) — enables Compression::Lz4. If enabled, Compression::Lz4 is used by default for all queries except for WATCH.
• inserter — enables client.inserter().
• test-util — adds mocks. See the example. Use it only in dev-dependencies.
• watch — enables client.watch functionality. See the corresponding section for details.
• uuid — adds serde::uuid to work with uuid crate.
• time — adds serde::time to work with time crate.

TLS

By default, TLS is disabled and one or more following features must be enabled to use HTTPS urls:

• native-tls — uses native-tls, utilizing dynamic linking (e.g. against OpenSSL).
• rustls-tls — enables rustls-tls-aws-lc and rustls-tls-webpki-roots features.
• rustls-tls-aws-lc — uses rustls with the aws-lc cryptography implementation.
• rustls-tls-ring — uses rustls with the ring cryptography implementation.
• rustls-tls-webpki-roots — uses rustls with certificates provided by the webpki-roots crate.
• rustls-tls-native-roots — uses rustls with certificates provided by the rustls-native-certs crate.

If multiple features are enabled, the following priority is applied:

• native-tls > rustls-tls-aws-lc > rustls-tls-ring
• rustls-tls-native-roots > rustls-tls-webpki-roots

How to choose between all these features? Here are some considerations:

• A good starting point is rustls-tls, e.g. if you use ClickHouse Cloud.
• To be more environment-agnostic, prefer rustls-tls over native-tls.
• Enable rustls-tls-native-roots or native-tls if you want to use self-signed certificates.

Data Types

• (U)Int(8|16|32|64|128) maps to/from corresponding (u|i)(8|16|32|64|128) types or newtypes around them.

• (U)Int256 aren't supported directly, but there is a workaround for it.

• Float(32|64) maps to/from corresponding f(32|64) or newtypes around them.

• Decimal(32|64|128) maps to/from corresponding i(32|64|128) or newtypes around them. It's more convenient to use fixnum or another implementation of signed fixed-point numbers.

• Boolean maps to/from bool or newtypes around it.

• String maps to/from any string or bytes types, e.g. &str, &[u8], String, Vec<u8> or SmartString. Newtypes are also supported. To store bytes, consider using serde_bytes, because it's more efficient.

  <details> <summary>Example</summary>

  #[derive(Row, Debug, Serialize, Deserialize)]
  struct MyRow<'a> {
      str: &'a str,
      string: String,
      #[serde(with = "serde_bytes")]
      bytes: Vec<u8>,
      #[serde(with = "serde_bytes")]
      byte_slice: &'a [u8],
  }
  

  </details>

• FixedString(N) is supported as an array of bytes, e.g. [u8; N].

  <details> <summary>Example</summary>

  #[derive(Row, Debug, Serialize, Deserialize)]
  struct MyRow {
      fixed_str: [u8; 16], // FixedString(16)
  }
  

  </details>

• Enum(8|16) are supported using serde_repr.

  <details> <summary>Example</summary>

  use serde_repr::{Deserialize_repr, Serialize_repr};
  
  #[derive(Row, Serialize, Deserialize)]
  struct MyRow {
      level: Level,
  }
  
  #[derive(Debug, Serialize_repr, Deserialize_repr)]
  #[repr(u8)]
  enum Level {
      Debug = 1,
      Info = 2,
      Warn = 3,
      Error = 4,
  }
  

  </details>

• UUID maps to/from uuid::Uuid by using serde::uuid. Requires the uuid feature.

  <details> <summary>Example</summary>

  #[derive(Row, Serialize, Deserialize)]
  struct MyRow {
      #[serde(with = "clickhouse::serde::uuid")]
      uuid: uuid::Uuid,
  }
  

  </details>

• IPv6 maps to/from std::net::Ipv6Addr.

• IPv4 maps to/from std::net::Ipv4Addr by using serde::ipv4.

  <details> <summary>Example</summary>

  #[derive(Row, Serialize, Deserialize)]
  struct MyRow {
      #[serde(with = "clickhouse::serde::ipv4")]
      ipv4: std::net::Ipv4Addr,
  }
  

  </details>

• Date maps to/from u16 or a newtype around it and represents a number of days elapsed since 1970-01-01. Also, time::Date is supported by using serde::time::date, that requires the time feature.

  <details> <summary>Example</summary>

  #[derive(Row, Serialize, Deserialize)]
  struct MyRow {
      days: u16,
      #[serde(with = "clickhouse::serde::time::date")]
      date: Date,
  }
  

  </details>

• Date32 maps to/from i32 or a newtype around it and represents a number of days elapsed since 1970-01-01. Also, time::Date is supported by using serde::time::date32, that requires the time feature.

  <details> <summary>Example</summary>

  #[derive(Row, Serialize, Deserialize)]
  struct MyRow {
      days: i32,
      #[serde(with = "clickhouse::serde::time::date32")]
      date: Date,
  }
  

  </details>

• DateTime maps to/from u32 or a newtype around it and represents a number of seconds elapsed since UNIX epoch. Also, time::OffsetDateTime is supported by using serde::time::datetime, that requires the time feature.

  <details> <summary>Example</summary>

  #[derive(Row, Serialize, Deserialize)]
  struct MyRow {
      ts: u32,
      #[serde(with = "clickhouse::serde::time::datetime")]
      dt: OffsetDateTime,
  }
  

  </details>

• DateTime64(_) maps to/from i32 or a newtype around it and represents a time elapsed since UNIX epoch. Also, time::OffsetDateTime is supported by using serde::time::datetime64::*, that requires the time feature.

  <details> <summary>Example</summary>

  #[derive(Row, Serialize, Deserialize)]
  struct MyRow {
      ts: i64, // elapsed s/us/ms/ns depending on `DateTime64(X)`
      #[serde(with = "clickhouse::serde::time::datetime64::secs")]
      dt64s: OffsetDateTime,  // `DateTime64(0)`
      #[serde(with = "clickhouse::serde::time::datetime64::millis")]
      dt64ms: OffsetDateTime, // `DateTime64(3)`
      #[serde(with = "clickhouse::serde::time::datetime64::micros")]
      dt64us: OffsetDateTime, // `DateTime64(6)`
      #[serde(with = "clickhouse::serde::time::datetime64::nanos")]
      dt64ns: OffsetDateTime, // `DateTime64(9)`
  }
  

  </details>

• Tuple(A, B, ...) maps to/from (A, B, ...) or a newtype around it.

• Array(_) maps to/from any slice, e.g. Vec<_>, &[_]. Newtypes are also supported.

• Map(K, V) behaves like Array((K, V)).

• LowCardinality(_) is supported seamlessly.

• Nullable(_) maps to/from Option<_>. For clickhouse::serde::* helpers add ::option.

  <details> <summary>Example</summary>

  #[derive(Row, Serialize, Deserialize)]
  struct MyRow {
      #[serde(with = "clickhouse::serde::ipv4::option")]
      ipv4_opt: Option<Ipv4Addr>,
  }
  

  </details>

• Nested is supported by providing multiple arrays with renaming.

  <details> <summary>Example</summary>

  // CREATE TABLE test(items Nested(name String, count UInt32))
  #[derive(Row, Serialize, Deserialize)]
  struct MyRow {
      #[serde(rename = "items.name")]
      items_name: Vec<String>,
      #[serde(rename = "items.count")]
      items_count: Vec<u32>,
  }
  

  </details>

• Geo types are supported. Point behaves like a tuple (f64, f64), and the rest of the types are just slices of points.

  <details> <summary>Example</summary>

  type Point = (f64, f64);
  type Ring = Vec<Point>;
  type Polygon = Vec<Ring>;
  type MultiPolygon = Vec<Polygon>;
  type LineString = Vec<Point>;
  type MultiLineString = Vec<LineString>;
  
  #[derive(Row, Serialize, Deserialize)]
  struct MyRow {
      point: Point,
      ring: Ring,
      polygon: Polygon,
      multi_polygon: MultiPolygon,
      line_string: LineString,
      multi_line_string: MultiLineString,
  }
  

  </details>

• New JSON data type is currently supported as a string when using ClickHouse 24.10+. See this example for more details.

• Variant, Dynamic types are not supported for now.

See also the additional examples:

• Simpler ClickHouse data types
• Container-like ClickHouse data types

Mocking

The crate provides utils for mocking CH server and testing DDL, SELECT, INSERT and WATCH queries.

The functionality can be enabled with the test-util feature. Use it only in dev-dependencies.

See the example.