Struct TensorBaseEventsBackend 

pub struct TensorBaseEventsBackend(/* private fields */);

Scale-out TensorBase structured-event storage over its ClickHouse-compatible protocol.

Use connect with a full protocol URL or connect_host for the default native port (9528). Pair this type with TensorBaseMetricsBackend when building the runtime.

Examples

Public crate wiring through Spectra::builder() (requires the spectra crate with the tensorbase feature):

use std::sync::Arc;
use spectra::{Spectra, TensorBaseEventsBackend, TensorBaseMetricsBackend};

let url = "tcp+tls://tensorbase.example:9440";
// Local plaintext: SPECTRA_ALLOW_INSECURE_REMOTE=1 + tcp://127.0.0.1:9528
let spectra = Spectra::builder()
    .metrics_backend(Arc::new(TensorBaseMetricsBackend::connect(url).await?))
    .events_backend(Arc::new(TensorBaseEventsBackend::connect(url).await?))
    .build()?;

Implementations

impl TensorBaseEventsBackend

pub async fn connect(url: &str) -> Result<TensorBaseEventsBackend, Error>

Connect with a full TensorBase protocol URL and ensure event tables exist.

Accepts tcp+tls:// / https:// (or plaintext tcp:// / http:// with SPECTRA_ALLOW_INSECURE_REMOTE=1). The call is async and executes DDL.

Examples

use spectra_backend_tensorbase::TensorBaseEventsBackend;

let backend = TensorBaseEventsBackend::connect("tcp+tls://127.0.0.1:9440").await?;

pub async fn connect_host(host: &str) -> Result<TensorBaseEventsBackend, Error>

Connect using a host name and the default native port (9528).

Equivalent to connect with tcp://{host}:9528 (requires SPECTRA_ALLOW_INSECURE_REMOTE=1 for that plaintext scheme).

Examples

use spectra_backend_tensorbase::TensorBaseEventsBackend;

let backend = TensorBaseEventsBackend::connect_host("127.0.0.1").await?;

pub fn in_memory_stub() -> TensorBaseEventsBackend

In-memory stub that preserves the TensorBase engine type for storage-contract tests.

Examples

use spectra_backend_tensorbase::TensorBaseEventsBackend;
use spectra_core::{EventStorageBackend, StorageEngineType};

let backend = TensorBaseEventsBackend::in_memory_stub();
assert_eq!(backend.engine_type(), StorageEngineType::TensorBase);

Trait Implementations

impl EventStorageBackend for TensorBaseEventsBackend

fn engine_type(&self) -> StorageEngineType

Returns the engine type for this backend.

fn append_row<'life0, 'life1, 'life2, 'life3, 'async_trait>( &'life0 self, table: &'life1 str, fields: &'life2 Value, ts: DateTime<Utc>, correlation_id: Option<&'life3 str>, ) -> Pin<Box<dyn Future<Output = Result<(), Error>> + Send + 'async_trait>>

where 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait, 'life3: 'async_trait, TensorBaseEventsBackend: 'async_trait,

Appends one event row.

fn append_rows_batch<'life0, 'life1, 'async_trait>( &'life0 self, rows: &'life1 [EventWriteRow], ) -> Pin<Box<dyn Future<Output = Result<(), Error>> + Send + 'async_trait>>

where 'life0: 'async_trait, 'life1: 'async_trait, TensorBaseEventsBackend: 'async_trait,

Batch append event rows (default: per-row dispatch).

fn query_rows<'life0, 'async_trait>( &'life0 self, filter: EventsQueryFilter, ) -> Pin<Box<dyn Future<Output = Result<Vec<EventRow>, Error>> + Send + 'async_trait>>

where 'life0: 'async_trait, TensorBaseEventsBackend: 'async_trait,

Queries event rows matching the filter.

fn query_aggregate<'life0, 'async_trait>( &'life0 self, filter: EventsAggregateFilter, ) -> Pin<Box<dyn Future<Output = Result<EventAggregateResult, Error>> + Send + 'async_trait>>

where 'life0: 'async_trait, TensorBaseEventsBackend: 'async_trait,

Queries aggregated chart data.