Upstream split the type and decoder half of the client into its own crate after
this fork was taken, which is why `datastore` is renamed here but every consumer
of `clickhouse-types` still had to name upstream to get it. insights/funnel-udf
is one: it reads `datastore_types::{Column, DataTypeNode}` out of a crate called
clickhouse-types, so the last upstream name in that repo was not one anybody had
missed -- it was one nothing in our tree provided.
Taken from upstream at 0.1.2, the version already in use, with the same two
dependencies and the sources rebranded. Five files.
Fields are spelled out rather than inherited. Upstream declares them
`authors.workspace = true`, which needs a `[workspace.package]` block at the
root; this fork's root is a plain package, and restructuring the whole manifest
to satisfy a five-file crate buys nothing.
`types` IS added as a workspace member, for a reason worth stating: cargo
resolves a git dependency by scanning the repo's workspace, so a directory no
manifest mentions cannot be found by one. Without that line the crate would be
present in the tree and unreachable to the only kind of dependency that can use
it -- `publish = false` here for the same reason as the root, since
`datastore-types` on crates.io is not ours either.
Verified: cargo check -p datastore-types builds it, and cargo check -p datastore
confirms the added workspace section leaves the root crate alone.
datastore-rs
Pure Rust typed client for Hanzo Datastore.
- Uses
serdefor encoding/decoding rows. - Supports
serdeattributes:skip_serializing,skip_deserializing,rename. - Uses
RowBinaryencoding over HTTP transport.- There are plans to switch to
Nativeover TCP.
- There are plans to switch to
- Supports TLS (see
native-tlsandrustls-tlsfeatures 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 (upstream) is useful to generate a row type from a table schema.
Usage
This crate is not published to crates.io — the datastore name there belongs
to an unrelated crate. Depend on it by git, pinned to a tag:
[dependencies]
datastore = { git = "https://github.com/hanzo-ds/rs", tag = "v0.13.3" }
[dev-dependencies]
datastore = { git = "https://github.com/hanzo-ds/rs", tag = "v0.13.3", features = ["test-util"] }
Note about Datastore prior to v22.6
CH server older than v22.6 (2022-06-16) handles RowBinary incorrectly (upstream issue #37420) 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 datastore::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 datastore::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
?fieldsis replaced withno, name(fields ofRow). - Placeholder
?is replaced with values in followingbind()calls. - Convenient
fetch_one::<Row>()andfetch_all::<Row>()can be used to get a first row or all rows correspondingly. sql::Identifiercan 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 datastore::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, theINSERTis aborted. - Rows are being sent progressively to spread network load.
- Datastore 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,
);
}
Please, read examples to understand how to use it properly in different real-world cases.
Inserterends an active insert incommit()if thresholds (max_bytes,max_rows,period) are reached.- The interval between ending active
INSERTs can be biased by usingwith_period_biasto avoid load spikes by parallel inserters. Inserter::time_left()can be used to detect when the current period ends. CallInserter::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-utilis enabled (thus, time can be managed bytokio::time::advance()in custom tests). - All rows between
commit()calls are inserted in the sameINSERTstatement. - 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 (see upstream issue #28309).
- 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
JSONEachRowWithProgressunder the hood because of upstream issue #22996. - Only struct rows can be used. Avoid
fetch::<u64>()and other without specified names.
See examples.
Feature Flags
lz4(enabled by default) — enablesCompression::Lz4. If enabled,Compression::Lz4is used by default for all queries except forWATCH.inserter— enablesclient.inserter().test-util— adds mocks. See the example. Use it only indev-dependencies.watch— enablesclient.watchfunctionality. See the corresponding section for details.uuid— addsserde::uuidto work with uuid crate.time— addsserde::timeto work with time crate.chrono— addsserde::chronoto work with chrono 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— enablesrustls-tls-aws-lcandrustls-tls-webpki-rootsfeatures.rustls-tls-aws-lc— uses rustls with theaws-lccryptography implementation.rustls-tls-ring— uses rustls with theringcryptography 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-ringrustls-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 Hanzo Datastore Cloud. - To be more environment-agnostic, prefer
rustls-tlsovernative-tls. - Enable
rustls-tls-native-rootsornative-tlsif 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)Int256aren't supported directly, but there is a workaround for it. -
Float(32|64)maps to/from correspondingf(32|64)or newtypes around them. -
Decimal(32|64|128)maps to/from correspondingi(32|64|128)or newtypes around them. It's more convenient to use fixnum or another implementation of signed fixed-point numbers. -
Booleanmaps to/fromboolor newtypes around it. -
Stringmaps to/from any string or bytes types, e.g.&str,&[u8],String,Vec<u8>orSmartString. Newtypes are also supported. To store bytes, consider using serde_bytes, because it's more efficient.Example
#[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], } -
FixedString(N)is supported as an array of bytes, e.g.[u8; N].Example
#[derive(Row, Debug, Serialize, Deserialize)] struct MyRow { fixed_str: [u8; 16], // FixedString(16) } -
Enum(8|16)are supported using serde_repr.Example
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, } -
UUIDmaps to/fromuuid::Uuidby usingserde::uuid. Requires theuuidfeature.Example
#[derive(Row, Serialize, Deserialize)] struct MyRow { #[serde(with = "datastore::serde::uuid")] uuid: uuid::Uuid, } -
IPv6maps to/fromstd::net::Ipv6Addr. -
IPv4maps to/fromstd::net::Ipv4Addrby usingserde::ipv4.Example
#[derive(Row, Serialize, Deserialize)] struct MyRow { #[serde(with = "datastore::serde::ipv4")] ipv4: std::net::Ipv4Addr, } -
Datemaps to/fromu16or a newtype around it and represents a number of days elapsed since1970-01-01. The following external types are supported:time::Dateis supported by usingserde::time::date, requiring thetimefeature.chrono::NaiveDateis supported by usingserde::chrono::date, requiring thechronofeature.
Example
#[derive(Row, Serialize, Deserialize)] struct MyRow { days: u16, #[serde(with = "datastore::serde::time::date")] date: Date, // if you prefer using chrono: #[serde(with = "datastore::serde::chrono::date")] date_chrono: NaiveDate, } -
Date32maps to/fromi32or a newtype around it and represents a number of days elapsed since1970-01-01. The following external types are supported:time::Dateis supported by usingserde::time::date32, requiring thetimefeature.chrono::NaiveDateis supported by usingserde::chrono::date32, requiring thechronofeature.
Example
#[derive(Row, Serialize, Deserialize)] struct MyRow { days: i32, #[serde(with = "datastore::serde::time::date32")] date: Date, // if you prefer using chrono: #[serde(with = "datastore::serde::chrono::date32")] date_chrono: NaiveDate, } -
DateTimemaps to/fromu32or a newtype around it and represents a number of seconds elapsed since UNIX epoch. The following external types are supported:time::OffsetDateTimeis supported by usingserde::time::datetime, requiring thetimefeature.chrono::DateTime<Utc>is supported by usingserde::chrono::datetime, requiring thechronofeature.
Example
#[derive(Row, Serialize, Deserialize)] struct MyRow { ts: u32, #[serde(with = "datastore::serde::time::datetime")] dt: OffsetDateTime, // if you prefer using chrono: #[serde(with = "datastore::serde::chrono::datetime")] dt_chrono: DateTime<Utc>, } -
DateTime64(_)maps to/fromi64or a newtype around it and represents a time elapsed since UNIX epoch. The following external types are supported:time::OffsetDateTimeis supported by usingserde::time::datetime64::*, requiring thetimefeature.chrono::DateTime<Utc>is supported by usingserde::chrono::datetime64::*, requiring thechronofeature.
Example
#[derive(Row, Serialize, Deserialize)] struct MyRow { ts: i64, // elapsed s/us/ms/ns depending on `DateTime64(X)` #[serde(with = "datastore::serde::time::datetime64::secs")] dt64s: OffsetDateTime, // `DateTime64(0)` #[serde(with = "datastore::serde::time::datetime64::millis")] dt64ms: OffsetDateTime, // `DateTime64(3)` #[serde(with = "datastore::serde::time::datetime64::micros")] dt64us: OffsetDateTime, // `DateTime64(6)` #[serde(with = "datastore::serde::time::datetime64::nanos")] dt64ns: OffsetDateTime, // `DateTime64(9)` // if you prefer using chrono: #[serde(with = "datastore::serde::chrono::datetime64::secs")] dt64s_chrono: DateTime<Utc>, // `DateTime64(0)` #[serde(with = "datastore::serde::chrono::datetime64::millis")] dt64ms_chrono: DateTime<Utc>, // `DateTime64(3)` #[serde(with = "datastore::serde::chrono::datetime64::micros")] dt64us_chrono: DateTime<Utc>, // `DateTime64(6)` #[serde(with = "datastore::serde::chrono::datetime64::nanos")] dt64ns_chrono: DateTime<Utc>, // `DateTime64(9)` } -
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 likeArray((K, V)). -
LowCardinality(_)is supported seamlessly. -
Nullable(_)maps to/fromOption<_>. Fordatastore::serde::*helpers add::option.Example
#[derive(Row, Serialize, Deserialize)] struct MyRow { #[serde(with = "datastore::serde::ipv4::option")] ipv4_opt: Option<Ipv4Addr>, } -
Nestedis supported by providing multiple arrays with renaming.Example
// 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>, } -
Geotypes are supported.Pointbehaves like a tuple(f64, f64), and the rest of the types are just slices of points.Example
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, } -
Variantdata type is supported as a Rust enum. As the inner Variant types are always sorted alphabetically, Rust enum variants should be defined in the exactly same order as it is in the data type; their names are irrelevant, only the order of the types matters. This following example has a column defined asVariant(Array(UInt16), Bool, Date, String, UInt32):Example
#[derive(Serialize, Deserialize)] enum MyRowVariant { Array(Vec<i16>), Boolean(bool), #[serde(with = "datastore::serde::time::date")] Date(time::Date), String(String), UInt32(u32), } #[derive(Row, Serialize, Deserialize)] struct MyRow { id: u64, var: MyRowVariant, } -
New
JSONdata type is currently supported as a string when using Datastore 24.10+. See this example for more details. -
Dynamicdata type is not supported for now.
See also the additional examples:
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.