mirror of
https://github.com/GreptimeTeam/greptimedb.git
synced 2025-12-27 16:32:54 +00:00
feat: flownode to frontend load balance with guess
This commit is contained in:
@@ -14,8 +14,9 @@
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//! Frontend client to run flow as batching task which is time-window-aware normal query triggered every tick set by user
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use std::sync::{Arc, Weak};
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use std::time::SystemTime;
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use std::collections::HashMap;
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use std::sync::{Arc, Mutex, Weak};
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use std::time::{Duration, Instant, SystemTime};
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use api::v1::greptime_request::Request;
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use api::v1::CreateTableExpr;
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@@ -26,20 +27,21 @@ use common_meta::cluster::{NodeInfo, NodeInfoKey, Role};
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use common_meta::peer::Peer;
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use common_meta::rpc::store::RangeRequest;
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use common_query::Output;
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use common_telemetry::warn;
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use common_telemetry::{debug, warn};
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use itertools::Itertools;
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use meta_client::client::MetaClient;
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use rand::rng;
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use rand::seq::SliceRandom;
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use servers::query_handler::grpc::GrpcQueryHandler;
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use session::context::{QueryContextBuilder, QueryContextRef};
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use snafu::{OptionExt, ResultExt};
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use crate::batching_mode::task::BatchingTask;
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use crate::batching_mode::{
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DEFAULT_BATCHING_ENGINE_QUERY_TIMEOUT, FRONTEND_ACTIVITY_TIMEOUT, GRPC_CONN_TIMEOUT,
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GRPC_MAX_RETRIES,
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};
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use crate::error::{ExternalSnafu, InvalidRequestSnafu, NoAvailableFrontendSnafu, UnexpectedSnafu};
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use crate::{Error, FlowAuthHeader};
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use crate::metrics::METRIC_FLOW_BATCHING_ENGINE_GUESS_FE_LOAD;
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use crate::{Error, FlowAuthHeader, FlowId};
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/// Just like [`GrpcQueryHandler`] but use BoxedError
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///
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@@ -74,6 +76,105 @@ impl<
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type HandlerMutable = Arc<std::sync::Mutex<Option<Weak<dyn GrpcQueryHandlerWithBoxedError>>>>;
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/// Statistics about running query on this frontend from flownode
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#[derive(Debug, Default, Clone)]
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struct FrontendStat {
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/// The query for flow id has been running since this timestamp
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since: HashMap<FlowId, Instant>,
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/// The average query time for each flow id
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/// This is used to calculate the average query time for each flow id
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past_query_avg: HashMap<FlowId, (usize, Duration)>,
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}
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#[derive(Debug, Default, Clone)]
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pub struct FrontendStats {
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/// The statistics for each flow id
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stats: Arc<Mutex<HashMap<String, FrontendStat>>>,
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}
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impl FrontendStats {
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pub fn observe(&self, frontend_addr: &str, flow_id: FlowId) -> FrontendStatsGuard {
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let mut stats = self.stats.lock().expect("Failed to lock frontend stats");
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let stat = stats.entry(frontend_addr.to_string()).or_default();
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stat.since.insert(flow_id, Instant::now());
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FrontendStatsGuard {
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stats: self.stats.clone(),
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frontend_addr: frontend_addr.to_string(),
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cur: flow_id,
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}
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}
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/// return frontend addrs sorted by load, from lightest to heaviest
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/// The load is calculated as the total average query time for each flow id plus running query's total running time elapsed
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pub fn sort_by_load(&self) -> Vec<String> {
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let stats = self.stats.lock().expect("Failed to lock frontend stats");
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let fe_load_factor = stats
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.iter()
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.map(|(node_addr, stat)| {
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// total expected avg running time for all currently running queries
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let total_expect_avg_run_time = stat
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.since
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.keys()
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.map(|f| {
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let (count, total_duration) =
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stat.past_query_avg.get(f).unwrap_or(&(0, Duration::ZERO));
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if *count == 0 {
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0.0
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} else {
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total_duration.as_secs_f64() / *count as f64
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}
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})
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.sum::<f64>();
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let total_cur_running_time = stat
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.since
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.values()
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.map(|since| since.elapsed().as_secs_f64())
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.sum::<f64>();
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(
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node_addr.to_string(),
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total_expect_avg_run_time + total_cur_running_time,
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)
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})
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.sorted_by(|(_, load_a), (_, load_b)| {
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load_a
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.partial_cmp(load_b)
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.unwrap_or(std::cmp::Ordering::Equal)
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})
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.collect::<Vec<_>>();
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debug!("Frontend load factor: {:?}", fe_load_factor);
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for (node_addr, load) in &fe_load_factor {
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METRIC_FLOW_BATCHING_ENGINE_GUESS_FE_LOAD
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.with_label_values(&[&node_addr.to_string()])
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.observe(*load);
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}
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fe_load_factor
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.into_iter()
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.map(|(addr, _)| addr)
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.collect::<Vec<_>>()
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}
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}
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pub struct FrontendStatsGuard {
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stats: Arc<Mutex<HashMap<String, FrontendStat>>>,
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frontend_addr: String,
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cur: FlowId,
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}
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impl Drop for FrontendStatsGuard {
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fn drop(&mut self) {
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let mut stats = self.stats.lock().expect("Failed to lock frontend stats");
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if let Some(stat) = stats.get_mut(&self.frontend_addr) {
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if let Some(since) = stat.since.remove(&self.cur) {
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let elapsed = since.elapsed();
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let (count, total_duration) = stat.past_query_avg.entry(self.cur).or_default();
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*count += 1;
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*total_duration += elapsed;
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}
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}
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}
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}
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/// A simple frontend client able to execute sql using grpc protocol
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///
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/// This is for computation-heavy query which need to offload computation to frontend, lifting the load from flownode
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@@ -83,6 +184,7 @@ pub enum FrontendClient {
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meta_client: Arc<MetaClient>,
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chnl_mgr: ChannelManager,
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auth: Option<FlowAuthHeader>,
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fe_stats: FrontendStats,
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},
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Standalone {
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/// for the sake of simplicity still use grpc even in standalone mode
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@@ -114,6 +216,7 @@ impl FrontendClient {
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ChannelManager::with_config(cfg)
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},
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auth,
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fe_stats: Default::default(),
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}
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}
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@@ -192,6 +295,7 @@ impl FrontendClient {
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meta_client: _,
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chnl_mgr,
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auth,
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fe_stats,
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} = self
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else {
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return UnexpectedSnafu {
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@@ -208,8 +312,21 @@ impl FrontendClient {
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.duration_since(SystemTime::UNIX_EPOCH)
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.unwrap()
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.as_millis() as i64;
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// shuffle the frontends to avoid always pick the same one
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frontends.shuffle(&mut rng());
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let node_addrs_by_load = fe_stats.sort_by_load();
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// index+1 to load order asc, so that the lightest node has load 1 and non-existent node has load 0
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let addr2load = node_addrs_by_load
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.iter()
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.enumerate()
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.map(|(i, id)| (id.clone(), i + 1))
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.collect::<HashMap<_, _>>();
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// sort frontends by load, from lightest to heaviest
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frontends.sort_by(|(_, a), (_, b)| {
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// if not even in stats, treat as 0 load since never been queried
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let load_a = addr2load.get(&a.peer.addr).unwrap_or(&0);
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let load_b = addr2load.get(&b.peer.addr).unwrap_or(&0);
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load_a.cmp(load_b)
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});
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debug!("Frontend nodes sorted by load: {:?}", frontends);
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// found node with maximum last_activity_ts
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for (_, node_info) in frontends
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@@ -257,6 +374,7 @@ impl FrontendClient {
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create: CreateTableExpr,
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catalog: &str,
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schema: &str,
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task: Option<&BatchingTask>,
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) -> Result<u32, Error> {
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self.handle(
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Request::Ddl(api::v1::DdlRequest {
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@@ -265,6 +383,7 @@ impl FrontendClient {
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catalog,
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schema,
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&mut None,
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task,
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)
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.await
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}
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@@ -276,15 +395,19 @@ impl FrontendClient {
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catalog: &str,
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schema: &str,
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peer_desc: &mut Option<PeerDesc>,
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task: Option<&BatchingTask>,
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) -> Result<u32, Error> {
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match self {
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FrontendClient::Distributed { .. } => {
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FrontendClient::Distributed { fe_stats, .. } => {
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let db = self.get_random_active_frontend(catalog, schema).await?;
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*peer_desc = Some(PeerDesc::Dist {
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peer: db.peer.clone(),
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});
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let flow_id = task.map(|t| t.config.flow_id).unwrap_or_default();
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let _guard = fe_stats.observe(&db.peer.addr, flow_id);
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db.database
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.handle_with_retry(req.clone(), GRPC_MAX_RETRIES)
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.await
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@@ -280,7 +280,7 @@ impl BatchingTask {
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let catalog = &self.config.sink_table_name[0];
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let schema = &self.config.sink_table_name[1];
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frontend_client
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.create(expr.clone(), catalog, schema)
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.create(expr.clone(), catalog, schema, Some(self))
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.await?;
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Ok(())
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}
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@@ -361,7 +361,7 @@ impl BatchingTask {
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};
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frontend_client
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.handle(req, catalog, schema, &mut peer_desc)
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.handle(req, catalog, schema, &mut peer_desc, Some(self))
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.await
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};
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@@ -58,6 +58,14 @@ lazy_static! {
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vec![60., 4. * 60., 16. * 60., 64. * 60., 256. * 60.]
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)
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.unwrap();
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pub static ref METRIC_FLOW_BATCHING_ENGINE_GUESS_FE_LOAD: HistogramVec =
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register_histogram_vec!(
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"greptime_flow_batching_engine_guess_fe_load",
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"flow batching engine guessed frontend load",
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&["fe_addr"],
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vec![60., 4. * 60., 16. * 60., 64. * 60., 256. * 60.]
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)
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.unwrap();
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pub static ref METRIC_FLOW_RUN_INTERVAL_MS: IntGauge =
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register_int_gauge!("greptime_flow_run_interval_ms", "flow run interval in ms").unwrap();
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pub static ref METRIC_FLOW_ROWS: IntCounterVec = register_int_counter_vec!(
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