/* Title: Pure/Tools/build_schedule.scala
Author: Fabian Huch, TU Muenchen
Build schedule generated by Heuristic methods, allowing for more efficient builds.
*/
package isabelle
import Host.Node_Info
import scala.annotation.tailrec
object Build_Schedule {
/* organized historic timing information (extracted from build logs) */
case class Timing_Entry(job_name: String, hostname: String, threads: Int, timing: Timing) {
def elapsed: Time = timing.elapsed
def proper_cpu: Option[Time] = timing.cpu.proper_ms.map(Time.ms)
}
case class Timing_Entries(entries: List[Timing_Entry]) {
require(entries.nonEmpty)
def is_empty = entries.isEmpty
def size = entries.length
lazy val by_job = entries.groupBy(_.job_name).view.mapValues(Timing_Entries(_)).toMap
lazy val by_threads = entries.groupBy(_.threads).view.mapValues(Timing_Entries(_)).toMap
lazy val by_hostname = entries.groupBy(_.hostname).view.mapValues(Timing_Entries(_)).toMap
def mean_time: Time = Timing_Data.mean_time(entries.map(_.elapsed))
def best_entry: Timing_Entry = entries.minBy(_.elapsed.ms)
}
class Timing_Data private(data: Timing_Entries, val host_infos: Host_Infos) {
private def inflection_point(last_mono: Int, next: Int): Int =
last_mono + ((next - last_mono) / 2)
def best_threads(job_name: String, max_threads: Int): Int = {
val worse_threads =
data.by_job.get(job_name).toList.flatMap(_.by_hostname).flatMap {
case (hostname, data) =>
val best_threads = data.best_entry.threads
data.by_threads.keys.toList.sorted.find(_ > best_threads).map(
inflection_point(best_threads, _))
}
(max_threads :: worse_threads).min
}
private def hostname_factor(from: String, to: String): Double =
host_infos.host_factor(host_infos.the_host(from), host_infos.the_host(to))
private def approximate_threads(entries_unsorted: List[(Int, Time)], threads: Int): Time = {
val entries = entries_unsorted.sortBy(_._1)
def sorted_prefix[A](xs: List[A], f: A => Long): List[A] =
xs match {
case x1 :: x2 :: xs =>
if (f(x1) <= f(x2)) x1 :: sorted_prefix(x2 :: xs, f) else x1 :: Nil
case xs => xs
}
def linear(p0: (Int, Time), p1: (Int, Time)): Time = {
val a = (p1._2 - p0._2).scale(1.0 / (p1._1 - p0._1))
val b = p0._2 - a.scale(p0._1)
Time.ms((a.scale(threads) + b).ms max 0)
}
val mono_prefix = sorted_prefix(entries, e => -e._2.ms)
val is_mono = entries == mono_prefix
val in_prefix = mono_prefix.length > 1 && threads <= mono_prefix.last._1
val in_inflection =
!is_mono && mono_prefix.length > 1 && threads < entries.drop(mono_prefix.length).head._1
if (is_mono || in_prefix || in_inflection) {
// Model with Amdahl's law
val t_p =
Timing_Data.median_time(for {
(n, t0) <- mono_prefix
(m, t1) <- mono_prefix
if m != n
} yield (t0 - t1).scale(n.toDouble * m / (m - n)))
val t_c =
Timing_Data.median_time(for ((n, t) <- mono_prefix) yield t - t_p.scale(1.0 / n))
def model(threads: Int): Time = Time.ms((t_c + t_p.scale(1.0 / threads)).ms max 0)
if (is_mono || in_prefix) model(threads)
else {
val post_inflection = entries.drop(mono_prefix.length).head
val inflection_threads = inflection_point(mono_prefix.last._1, post_inflection._1)
if (threads <= inflection_threads) model(threads)
else linear((inflection_threads, model(inflection_threads)), post_inflection)
}
} else {
// Piecewise linear
val (p0, p1) =
if (entries.head._1 < threads && threads < entries.last._1) {
val split = entries.partition(_._1 < threads)
(split._1.last, split._2.head)
} else {
val piece = if (threads < entries.head._1) entries.take(2) else entries.takeRight(2)
(piece.head, piece.last)
}
linear(p0, p1)
}
}
private def unify_hosts(job_name: String, on_host: String): List[(Int, Time)] = {
def unify(hostname: String, data: Timing_Entries) =
data.mean_time.scale(hostname_factor(hostname, on_host))
for {
data <- data.by_job.get(job_name).toList
(threads, data) <- data.by_threads
entries = data.by_hostname.toList.map(unify)
} yield threads -> Timing_Data.median_time(entries)
}
def estimate_threads(job_name: String, hostname: String, threads: Int): Option[Time] = {
def try_approximate(data: Timing_Entries): Option[Time] = {
val entries =
data.by_threads.toList match {
case List((i, Timing_Entries(List(entry)))) if i != 1 =>
(i, data.mean_time) :: entry.proper_cpu.map(1 -> _).toList
case entries => entries.map((threads, data) => threads -> data.mean_time)
}
if (entries.size < 2) None else Some(approximate_threads(entries, threads))
}
for {
data <- data.by_job.get(job_name)
data <- data.by_hostname.get(hostname)
time <- data.by_threads.get(threads).map(_.mean_time).orElse(try_approximate(data))
} yield time
}
def global_threads_factor(from: Int, to: Int): Double = {
def median(xs: Iterable[Double]): Double = xs.toList.sorted.apply(xs.size / 2)
val estimates =
for {
(hostname, data) <- data.by_hostname
job_name <- data.by_job.keys
from_time <- estimate_threads(job_name, hostname, from)
to_time <- estimate_threads(job_name, hostname, to)
} yield from_time.ms.toDouble / to_time.ms
if (estimates.nonEmpty) median(estimates)
else {
// unify hosts
val estimates =
for {
(job_name, data) <- data.by_job
hostname = data.by_hostname.keys.head
entries = unify_hosts(job_name, hostname)
if entries.length > 1
} yield
approximate_threads(entries, from).ms.toDouble / approximate_threads(entries, to).ms
if (estimates.nonEmpty) median(estimates)
else from.toDouble / to.toDouble
}
}
def estimate(job_name: String, hostname: String, threads: Int): Time =
data.by_job.get(job_name) match {
case None =>
// no data for job, take average of other jobs for given threads
val job_estimates = data.by_job.keys.flatMap(estimate_threads(_, hostname, threads))
if (job_estimates.nonEmpty) Timing_Data.mean_time(job_estimates)
else {
// no other job to estimate from, use global curve to approximate any other job
val (threads1, data1) = data.by_threads.head
data1.mean_time.scale(global_threads_factor(threads1, threads))
}
case Some(data) =>
data.by_threads.get(threads) match {
case None => // interpolate threads
estimate_threads(job_name, hostname, threads).getOrElse {
// per machine, try to approximate config for threads
val approximated =
for {
hostname1 <- data.by_hostname.keys
estimate <- estimate_threads(job_name, hostname1, threads)
factor = hostname_factor(hostname1, hostname)
} yield estimate.scale(factor)
if (approximated.nonEmpty) Timing_Data.mean_time(approximated)
else {
// no single machine where config can be approximated, unify data points
val unified_entries = unify_hosts(job_name, hostname)
if (unified_entries.length > 1) approximate_threads(unified_entries, threads)
else {
// only single data point, use global curve to approximate
val (job_threads, job_time) = unified_entries.head
job_time.scale(global_threads_factor(job_threads, threads))
}
}
}
case Some(data) => // time for job/thread exists, interpolate machine
data.by_hostname.get(hostname).map(_.mean_time).getOrElse {
Timing_Data.median_time(
data.by_hostname.toList.map((hostname1, data) =>
data.mean_time.scale(hostname_factor(hostname1, hostname))))
}
}
}
}
object Timing_Data {
def median_timing(obs: List[Timing]): Timing = obs.sortBy(_.elapsed.ms).apply(obs.length / 2)
def median_time(obs: List[Time]): Time = obs.sortBy(_.ms).apply(obs.length / 2)
def mean_time(obs: Iterable[Time]): Time = Time.ms(obs.map(_.ms).sum / obs.size)
private def dummy_entries(host: Host, host_factor: Double) = {
val baseline = Time.minutes(5).scale(host_factor)
val gc = Time.seconds(10).scale(host_factor)
List(
Timing_Entry("dummy", host.info.hostname, 1, Timing(baseline, baseline, gc)),
Timing_Entry("dummy", host.info.hostname, 8, Timing(baseline.scale(0.2), baseline, gc)))
}
def make(
host_infos: Host_Infos,
build_history: List[(Build_Log.Meta_Info, Build_Log.Build_Info)],
): Timing_Data = {
val hosts = host_infos.hosts
val measurements =
for {
(meta_info, build_info) <- build_history
build_host = meta_info.get(Build_Log.Prop.build_host)
(job_name, session_info) <- build_info.sessions.toList
if build_info.finished_sessions.contains(job_name)
hostname <- session_info.hostname.orElse(build_host).toList
host <- hosts.find(_.info.hostname == hostname).toList
threads = session_info.threads.getOrElse(host.info.num_cpus)
} yield (job_name, hostname, threads) -> session_info.timing
val entries =
if (measurements.isEmpty) {
val default_host = host_infos.hosts.sorted(host_infos.host_speeds).last
host_infos.hosts.flatMap(host =>
dummy_entries(host, host_infos.host_factor(default_host, host)))
}
else
measurements.groupMap(_._1)(_._2).toList.map {
case ((job_name, hostname, threads), timings) =>
Timing_Entry(job_name, hostname, threads, median_timing(timings))
}
new Timing_Data(Timing_Entries(entries), host_infos)
}
def load(host_infos: Host_Infos, log_database: SQL.Database): Timing_Data = {
val build_history =
for {
log_name <- log_database.execute_query_statement(
Build_Log.private_data.meta_info_table.select(List(Build_Log.Column.log_name)),
List.from[String], res => res.string(Build_Log.Column.log_name))
meta_info <- Build_Log.private_data.read_meta_info(log_database, log_name)
build_info = Build_Log.private_data.read_build_info(log_database, log_name)
} yield (meta_info, build_info)
make(host_infos, build_history)
}
}
/* host information */
case class Host(info: isabelle.Host.Info, build: Build_Cluster.Host)
object Host_Infos {
def dummy: Host_Infos =
new Host_Infos(
List(Host(isabelle.Host.Info("dummy", Nil, 8, Some(1.0)), Build_Cluster.Host("dummy"))))
def load(build_hosts: List[Build_Cluster.Host], db: SQL.Database): Host_Infos = {
def get_host(build_host: Build_Cluster.Host): Host = {
val info =
isabelle.Host.read_info(db, build_host.name).getOrElse(
error("No benchmark for " + quote(build_host.name)))
Host(info, build_host)
}
new Host_Infos(build_hosts.map(get_host))
}
}
class Host_Infos private(val hosts: List[Host]) {
require(hosts.nonEmpty)
private val by_hostname = hosts.map(host => host.info.hostname -> host).toMap
def host_factor(from: Host, to: Host): Double =
from.info.benchmark_score.get / to.info.benchmark_score.get
val host_speeds: Ordering[Host] =
Ordering.fromLessThan((host1, host2) => host_factor(host1, host2) < 1)
def the_host(hostname: String): Host =
by_hostname.getOrElse(hostname, error("Unknown host " + quote(hostname)))
def the_host(node_info: Node_Info): Host = the_host(node_info.hostname)
def num_threads(node_info: Node_Info): Int =
if (node_info.rel_cpus.nonEmpty) node_info.rel_cpus.length
else the_host(node_info).info.num_cpus
def available(state: Build_Process.State): Resources = {
val allocated =
state.running.values.map(_.node_info).groupMapReduce(the_host)(List(_))(_ ::: _)
Resources(this, allocated)
}
}
/* offline tracking of job configurations and resource allocations */
object Config {
def from_job(job: Build_Process.Job): Config = Config(job.name, job.node_info)
}
case class Config(job_name: String, node_info: Node_Info) {
def job_of(start_time: Time): Build_Process.Job =
Build_Process.Job(job_name, "", "", node_info, Date(start_time), None)
}
case class Resources(
host_infos: Host_Infos,
allocated_nodes: Map[Host, List[Node_Info]]
) {
def unused_nodes(threads: Int): List[Node_Info] = {
val fully_allocated =
host_infos.hosts.foldLeft(this) { case (resources, host) =>
if (!resources.available(host, threads)) resources
else resources.allocate(resources.next_node(host, threads))
}
val used_nodes = allocated_nodes.values.flatten.toSet
fully_allocated.allocated_nodes.values.flatten.toList.filterNot(used_nodes.contains)
}
def allocated(host: Host): List[Node_Info] = allocated_nodes.getOrElse(host, Nil)
def allocate(node: Node_Info): Resources = {
val host = host_infos.the_host(node)
copy(allocated_nodes = allocated_nodes + (host -> (node :: allocated(host))))
}
def try_allocate_tasks(
hosts: List[(Host, Int)],
tasks: List[(Build_Process.Task, Int, Int)],
): (List[Config], Resources) =
tasks match {
case Nil => (Nil, this)
case (task, min_threads, max_threads) :: tasks =>
val (config, resources) =
hosts.find((host, _) => available(host, min_threads)) match {
case Some((host, host_max_threads)) =>
val free_threads = host.info.num_cpus - ((host.build.jobs - 1) * host_max_threads)
val node_info = next_node(host, (min_threads max free_threads) min max_threads)
(Some(Config(task.name, node_info)), allocate(node_info))
case None => (None, this)
}
val (configs, resources1) = resources.try_allocate_tasks(hosts, tasks)
(configs ++ config, resources1)
}
def next_node(host: Host, threads: Int): Node_Info = {
val numa_node_num_cpus = host.info.num_cpus / (host.info.numa_nodes.length max 1)
def explicit_cpus(node_info: Node_Info): List[Int] =
if (node_info.rel_cpus.nonEmpty) node_info.rel_cpus else (0 until numa_node_num_cpus).toList
val used_nodes = allocated(host).groupMapReduce(_.numa_node)(explicit_cpus)(_ ::: _)
val available_nodes = host.info.numa_nodes
val numa_node =
if (!host.build.numa) None
else available_nodes.sortBy(n => used_nodes.getOrElse(Some(n), Nil).length).headOption
val used_cpus = used_nodes.getOrElse(numa_node, Nil).toSet
val available_cpus = (0 until numa_node_num_cpus).filterNot(used_cpus.contains).toList
val rel_cpus = if (available_cpus.length >= threads) available_cpus.take(threads) else Nil
Node_Info(host.info.hostname, numa_node, rel_cpus)
}
def available(host: Host, threads: Int): Boolean = {
val used = allocated(host)
if (used.length >= host.build.jobs) false
else {
if (host.info.numa_nodes.length <= 1)
used.map(host_infos.num_threads).sum + threads <= host.info.num_cpus
else {
def node_threads(n: Int): Int =
used.filter(_.numa_node.contains(n)).map(host_infos.num_threads).sum
host.info.numa_nodes.exists(
node_threads(_) + threads <= host.info.num_cpus / host.info.numa_nodes.length)
}
}
}
}
/* schedule generation */
object Schedule {
case class Node(job_name: String, node_info: Node_Info, start: Date, duration: Time) {
def end: Date = Date(start.time + duration)
}
type Graph = isabelle.Graph[String, Node]
}
case class Schedule(start: Date, graph: Schedule.Graph) {
def end: Date =
if (graph.is_empty) start
else graph.maximals.map(graph.get_node).map(_.end).maxBy(_.unix_epoch)
def duration: Time = end.time - start.time
}
case class State(build_state: Build_Process.State, current_time: Time, finished: Schedule) {
def start(config: Config): State =
copy(build_state =
build_state.copy(running = build_state.running +
(config.job_name -> config.job_of(current_time))))
def step(timing_data: Timing_Data): State = {
val remaining =
build_state.running.values.toList.map { job =>
val elapsed = current_time - job.start_date.time
val threads = timing_data.host_infos.num_threads(job.node_info)
val predicted = timing_data.estimate(job.name, job.node_info.hostname, threads)
val remaining = if (elapsed > predicted) Time.zero else predicted - elapsed
job -> remaining
}
if (remaining.isEmpty) error("Schedule step without running sessions")
else {
val (job, elapsed) = remaining.minBy(_._2.ms)
val now = current_time + elapsed
val node = Schedule.Node(job.name, job.node_info, job.start_date, now - job.start_date.time)
val preds =
build_state.sessions.graph.imm_preds(job.name).filter(finished.graph.defined)
val graph =
preds.foldLeft(finished.graph.new_node(job.name, node))(_.add_edge(_, job.name))
val build_state1 = build_state.remove_running(job.name).remove_pending(job.name)
State(build_state1, now, finished.copy(graph = graph))
}
}
def is_finished: Boolean = build_state.pending.isEmpty && build_state.running.isEmpty
}
trait Scheduler {
def next(state: Build_Process.State): List[Config]
def build_schedule(build_state: Build_Process.State): Schedule
}
abstract class Heuristic(timing_data: Timing_Data) extends Scheduler {
val host_infos = timing_data.host_infos
val ordered_hosts = host_infos.hosts.sorted(host_infos.host_speeds)
def build_schedule(build_state: Build_Process.State): Schedule = {
@tailrec
def simulate(state: State): State =
if (state.is_finished) state
else {
val state1 = next(state.build_state).foldLeft(state)(_.start(_)).step(timing_data)
simulate(state1)
}
val start = Date.now()
val end_state = simulate(State(build_state, start.time, Schedule(start, Graph.empty)))
end_state.finished
}
}
class Meta_Heuristic(heuristics: List[Heuristic]) extends Scheduler {
require(heuristics.nonEmpty)
def best_result(state: Build_Process.State): (Heuristic, Schedule) =
heuristics.map(heuristic =>
heuristic -> heuristic.build_schedule(state)).minBy(_._2.duration.ms)
def next(state: Build_Process.State): List[Config] = best_result(state)._1.next(state)
def build_schedule(state: Build_Process.State): Schedule = best_result(state)._2
}
/* heuristics */
abstract class Path_Heuristic(
timing_data: Timing_Data,
sessions_structure: Sessions.Structure,
max_threads_limit: Int
) extends Heuristic(timing_data) {
/* pre-computed properties for efficient heuristic */
val max_threads = host_infos.hosts.map(_.info.num_cpus).max min max_threads_limit
type Node = String
val build_graph = sessions_structure.build_graph
val minimals = build_graph.minimals
val maximals = build_graph.maximals
def all_preds(node: Node): Set[Node] = build_graph.all_preds(List(node)).toSet
val maximals_all_preds = maximals.map(node => node -> all_preds(node)).toMap
def best_time(node: Node): Time = {
val host = ordered_hosts.last
val threads = timing_data.best_threads(node, max_threads) min host.info.num_cpus
timing_data.estimate(node, host.info.hostname, threads)
}
val best_times = build_graph.keys.map(node => node -> best_time(node)).toMap
val succs_max_time_ms = build_graph.node_height(best_times(_).ms)
def max_time(node: Node): Time = Time.ms(succs_max_time_ms(node)) + best_times(node)
def max_time(task: Build_Process.Task): Time = max_time(task.name)
def path_times(minimals: List[Node]): Map[Node, Time] = {
def time_ms(node: Node): Long = best_times(node).ms
val path_times_ms = build_graph.reachable_length(time_ms, build_graph.imm_succs, minimals)
path_times_ms.view.mapValues(Time.ms).toMap
}
def path_max_times(minimals: List[Node]): Map[Node, Time] =
path_times(minimals).toList.map((node, time) => node -> (time + max_time(node))).toMap
def parallel_paths(minimals: List[Node], pred: Node => Boolean = _ => true): Int = {
def start(node: Node): (Node, Time) = node -> best_times(node)
def pass_time(elapsed: Time)(node: Node, time: Time): (Node, Time) =
node -> (time - elapsed)
def parallel_paths(running: Map[Node, Time]): (Int, Map[Node, Time]) =
if (running.isEmpty) (0, running)
else {
def get_next(node: Node): List[Node] =
build_graph.imm_succs(node).filter(pred).filter(
build_graph.imm_preds(_).intersect(running.keySet).isEmpty).toList
val (next, elapsed) = running.minBy(_._2.ms)
val (remaining, finished) =
running.toList.map(pass_time(elapsed)).partition(_._2 > Time.zero)
val running1 =
remaining.map(pass_time(elapsed)).toMap ++
finished.map(_._1).flatMap(get_next).map(start)
val (res, running2) = parallel_paths(running1)
(res max running1.size, running2)
}
parallel_paths(minimals.map(start).toMap)._1
}
}
class Timing_Heuristic(
threshold: Time,
timing_data: Timing_Data,
sessions_structure: Sessions.Structure,
max_threads_limit: Int = 8
) extends Path_Heuristic(timing_data, sessions_structure, max_threads_limit) {
def next(state: Build_Process.State): List[Config] = {
val resources = host_infos.available(state)
def best_threads(task: Build_Process.Task): Int =
timing_data.best_threads(task.name, max_threads)
val rev_ordered_hosts = ordered_hosts.reverse.map(_ -> max_threads)
val resources0 = host_infos.available(state.copy(running = Map.empty))
val max_parallel = parallel_paths(state.ready.map(_.name))
val fully_parallelizable = max_parallel <= resources0.unused_nodes(max_threads).length
val next_sorted = state.next_ready.sortBy(max_time(_).ms).reverse
if (fully_parallelizable) {
val all_tasks = next_sorted.map(task => (task, best_threads(task), best_threads(task)))
resources.try_allocate_tasks(rev_ordered_hosts, all_tasks)._1
}
else {
val critical_minimals = state.ready.filter(max_time(_) > threshold).map(_.name)
val critical_nodes = path_max_times(critical_minimals).filter(_._2 > threshold).keySet
val (critical, other) = next_sorted.partition(task => critical_nodes.contains(task.name))
val critical_tasks = critical.map(task => (task, best_threads(task), best_threads(task)))
val other_tasks = other.map(task => (task, 1, best_threads(task)))
val max_critical_parallel = parallel_paths(critical_minimals, critical_nodes.contains)
val (critical_hosts, other_hosts) = rev_ordered_hosts.splitAt(max_critical_parallel)
val (configs1, resources1) = resources.try_allocate_tasks(critical_hosts, critical_tasks)
val (configs2, _) = resources1.try_allocate_tasks(other_hosts, other_tasks)
configs1 ::: configs2
}
}
}
/* process for scheduled build */
abstract class Scheduled_Build_Process(
build_context: Build.Context,
build_progress: Progress,
server: SSH.Server,
) extends Build_Process(build_context, build_progress, server) {
protected val start_date = Date.now()
def init_scheduler(timing_data: Timing_Data): Scheduler
/* global resources with common close() operation */
private final lazy val _log_store: Build_Log.Store = Build_Log.store(build_options)
private final lazy val _log_database: SQL.Database =
try {
val db = _log_store.open_database(server = this.server)
_log_store.init_database(db)
db
}
catch { case exn: Throwable => close(); throw exn }
override def close(): Unit = {
super.close()
Option(_log_database).foreach(_.close())
}
/* previous results via build log */
override def open_build_cluster(): Build_Cluster = {
val build_cluster = super.open_build_cluster()
build_cluster.init()
if (build_context.master && build_context.max_jobs > 0) {
val benchmark_options = build_options.string("build_hostname") = hostname
Benchmark.benchmark(benchmark_options, progress)
}
build_cluster.benchmark()
build_cluster
}
private val timing_data: Timing_Data = {
val cluster_hosts: List[Build_Cluster.Host] =
if (build_context.max_jobs == 0) build_context.build_hosts
else {
val local_build_host =
Build_Cluster.Host(
hostname, jobs = build_context.max_jobs, numa = build_context.numa_shuffling)
local_build_host :: build_context.build_hosts
}
val host_infos = Host_Infos.load(cluster_hosts, _host_database)
Timing_Data.load(host_infos, _log_database)
}
private val scheduler = init_scheduler(timing_data)
def write_build_log(results: Build.Results, state: Build_Process.State.Results): Unit = {
val sessions =
for {
(session_name, result) <- state.toList
if !result.current
} yield {
val info = build_context.sessions_structure(session_name)
val entry =
if (!results.cancelled(session_name)) {
val status =
if (result.ok) Build_Log.Session_Status.finished
else Build_Log.Session_Status.failed
Build_Log.Session_Entry(
chapter = info.chapter,
groups = info.groups,
hostname = Some(result.node_info.hostname),
threads = Some(timing_data.host_infos.num_threads(result.node_info)),
timing = result.process_result.timing,
sources = Some(result.output_shasum.digest.toString),
status = Some(status))
}
else
Build_Log.Session_Entry(
chapter = info.chapter,
groups = info.groups,
status = Some(Build_Log.Session_Status.cancelled))
session_name -> entry
}
val settings =
Build_Log.Settings.all_settings.map(_.name).map(name =>
name -> Isabelle_System.getenv(name))
val props =
List(
Build_Log.Prop.build_id.name -> build_context.build_uuid,
Build_Log.Prop.build_engine.name -> build_context.engine.name,
Build_Log.Prop.build_host.name -> hostname,
Build_Log.Prop.build_start.name -> Build_Log.print_date(start_date))
val meta_info = Build_Log.Meta_Info(props, settings)
val build_info = Build_Log.Build_Info(sessions.toMap)
val log_name = Build_Log.log_filename(engine = build_context.engine.name, date = start_date)
Build_Log.private_data.update_sessions(
_log_database, _log_store.cache.compress, log_name.file_name, build_info)
Build_Log.private_data.update_meta_info(_log_database, log_name.file_name, meta_info)
}
/* build process */
case class Cache(state: Build_Process.State, configs: List[Config], estimate: Date) {
def is_current(state: Build_Process.State): Boolean =
this.state.pending.nonEmpty && this.state.results == state.results
def is_current_estimate(estimate: Date): Boolean =
Math.abs((this.estimate.time - estimate.time).ms) < Time.minutes(1).ms
}
private var cache = Cache(Build_Process.State(), Nil, Date.now())
override def next_node_info(state: Build_Process.State, session_name: String): Node_Info = {
val configs =
if (cache.is_current(state)) cache.configs
else scheduler.next(state)
configs.find(_.job_name == session_name).get.node_info
}
def is_current(state: Build_Process.State, session_name: String): Boolean =
state.ancestor_results(session_name) match {
case Some(ancestor_results) if ancestor_results.forall(_.current) =>
val sources_shasum = state.sessions(session_name).sources_shasum
val input_shasum =
if (ancestor_results.isEmpty) ML_Process.bootstrap_shasum()
else SHA1.flat_shasum(ancestor_results.map(_.output_shasum))
val store_heap =
build_context.build_heap || Sessions.is_pure(session_name) ||
state.sessions.iterator.exists(_.ancestors.contains(session_name))
store.check_output(
_database_server, session_name,
session_options = build_context.sessions_structure(session_name).options,
sources_shasum = sources_shasum,
input_shasum = input_shasum,
fresh_build = build_context.fresh_build,
store_heap = store_heap)._1
case _ => false
}
override def next_jobs(state: Build_Process.State): List[String] = {
val finalize_limit = if (build_context.master) Int.MaxValue else 0
if (progress.stopped) state.next_ready.map(_.name).take(finalize_limit)
else if (cache.is_current(state)) cache.configs.map(_.job_name).filterNot(state.is_running)
else {
val current = state.next_ready.filter(task => is_current(state, task.name))
if (current.nonEmpty) current.map(_.name).take(finalize_limit)
else {
val start = Time.now()
val next = scheduler.next(state)
val estimate = Date(Time.now() + scheduler.build_schedule(state).duration)
val elapsed = Time.now() - start
val timing_msg = if (elapsed.is_relevant) " (took " + elapsed.message + ")" else ""
progress.echo_if(build_context.master && !cache.is_current_estimate(estimate),
"Estimated completion: " + estimate + timing_msg)
val configs = next.filter(_.node_info.hostname == hostname)
cache = Cache(state, configs, estimate)
configs.map(_.job_name)
}
}
}
override def run(): Build.Results = {
val results = super.run()
if (build_context.master) write_build_log(results, snapshot().results)
results
}
}
class Engine extends Build.Engine("build_schedule") {
def scheduler(timing_data: Timing_Data, sessions_structure: Sessions.Structure): Scheduler = {
val heuristics =
List(5, 10, 20).map(minutes =>
Timing_Heuristic(Time.minutes(minutes), timing_data, sessions_structure))
new Meta_Heuristic(heuristics)
}
override def open_build_process(
context: Build.Context,
progress: Progress,
server: SSH.Server
): Build_Process =
new Scheduled_Build_Process(context, progress, server) {
def init_scheduler(timing_data: Timing_Data): Scheduler =
scheduler(timing_data, context.sessions_structure)
}
}
/* build schedule */
def build_schedule(
options: Options,
build_hosts: List[Build_Cluster.Host] = Nil,
selection: Sessions.Selection = Sessions.Selection.empty,
progress: Progress = new Progress,
afp_root: Option[Path] = None,
dirs: List[Path] = Nil,
select_dirs: List[Path] = Nil,
infos: List[Sessions.Info] = Nil,
numa_shuffling: Boolean = false,
augment_options: String => List[Options.Spec] = _ => Nil,
session_setup: (String, Session) => Unit = (_, _) => (),
cache: Term.Cache = Term.Cache.make()
): Schedule = {
val build_engine = new Engine
val store = build_engine.build_store(options, build_hosts = build_hosts, cache = cache)
val log_store = Build_Log.store(options, cache = cache)
val build_options = store.options
def build_schedule(
server: SSH.Server,
database_server: Option[SQL.Database],
log_database: PostgreSQL.Database,
host_database: SQL.Database
): Schedule = {
val full_sessions =
Sessions.load_structure(build_options, dirs = AFP.make_dirs(afp_root) ::: dirs,
select_dirs = select_dirs, infos = infos, augment_options = augment_options)
val full_sessions_selection = full_sessions.imports_selection(selection)
val build_deps =
Sessions.deps(full_sessions.selection(selection), progress = progress,
inlined_files = true).check_errors
val build_context =
Build.Context(store, build_engine, build_deps, afp_root = afp_root,
build_hosts = build_hosts, hostname = Build.hostname(build_options),
numa_shuffling = numa_shuffling, max_jobs = 0, session_setup = session_setup,
master = true)
val cluster_hosts = build_context.build_hosts
val hosts_current =
cluster_hosts.forall(host => isabelle.Host.read_info(host_database, host.name).isDefined)
if (!hosts_current) {
val build_cluster = Build_Cluster.make(build_context, progress = progress)
build_cluster.open()
build_cluster.init()
build_cluster.benchmark()
build_cluster.close()
}
val host_infos = Host_Infos.load(cluster_hosts, host_database)
val timing_data = Timing_Data.load(host_infos, log_database)
val sessions = Build_Process.Sessions.empty.init(build_context, database_server, progress)
def task(session: Build_Job.Session_Context): Build_Process.Task =
Build_Process.Task(session.name, session.deps, JSON.Object.empty, build_context.build_uuid)
val build_state =
Build_Process.State(sessions = sessions, pending = sessions.iterator.map(task).toList)
val scheduler = build_engine.scheduler(timing_data, build_context.sessions_structure)
scheduler.build_schedule(build_state)
}
using(store.open_server()) { server =>
using_optional(store.maybe_open_database_server(server = server)) { database_server =>
using(log_store.open_database(server = server)) { log_database =>
using(store.open_build_database(
path = isabelle.Host.private_data.database, server = server)) { host_database =>
build_schedule(server, database_server, log_database, host_database)
}
}
}
}
}
}