Files
windmill/backend/windmill-worker/src/bigquery_executor.rs
T
Ruben Fiszel a6d4390790 feat: workflow-as-code (WAC) v2 (#8172)
* feat: workflow-as-code v2 with @task decorator API

Replace ctx.step("name", "script") API with @task decorators where
functions are called directly. Users no longer need to pass WorkflowCtx
or use string-based step names/script paths.

Python: @task decorator with contextvars-based implicit context
TypeScript: task() wrapper with module-level context variable
Parsers: detect @task function calls instead of ctx.step() calls
Worker: updated wrappers to set implicit context

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: WAC v2 checkpoint/replay with _executing_key child dispatch

- Rust-side orchestration: parent dispatches child jobs, suspends, resumes on completion
- _executing_key in checkpoint tells child which step to execute directly
- task() throws StepSuspend(mode="step_complete") after executing target step
- result_processor handles child completion and updates parent checkpoint
- WacGraph.svelte for runtime execution visualization
- Sequential and parallel workflows tested end-to-end

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: WAC v2 bundle cache, globalThis ctx sharing, description optional

- Disable bun bundle caching for WAC v2 scripts (wrapper needs
  windmill-client from node_modules, not available in bundle mode)
- Use Reflect.set/get(globalThis, "__wmill_wf_ctx") to share workflow
  context across dual module instances (wrapper vs user script)
- Never-resolving thenable for non-matching steps in child job mode
  prevents Promise.all race conditions
- Make description field optional in NewScript API (defaults to "")

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: add step() primitive for inline checkpointed steps

step() executes a function inline (no child job) and persists the result
to the checkpoint. On replay, the cached value is returned — ensuring
deterministic behavior for non-deterministic operations like Date.now()
or Math.random().

- TypeScript: step(name, fn) — executes inline, throws StepSuspend with
  mode "inline_checkpoint" to persist before continuing
- Rust: InlineCheckpoint variant in WacOutput, saves to checkpoint and
  resets running=false for immediate re-pickup (no zombie wait)
- Shared step counter between task() and step() via _allocKey()

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: add Python WAC v2 support with task(), step(), workflow()

- Python SDK: WorkflowCtx with _executing_key child mode, _alloc_key
  shared counter, _run_inline_step for step(), _execute_directly and
  _never_resolve for child mode, step() async function
- Python executor: WAC v2 detection, checkpoint.json writing, WAC
  wrapper.py generation calling _run_workflow(), post-execution hook
  into shared handle_wac_v2_output()
- Make handle_wac_v2_output pub so both bun and python executors share
  the same dispatch/suspend/inline-checkpoint logic
- 17 Python tests covering dispatch, replay, parallel, conditional,
  inline checkpoint, and child mode

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* chore: update sqlx prepared queries

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: WacGraph Tooltip→Popover, simplify wacToFlow parsers

- Fix type error: Tooltip doesn't accept text snippet, use Popover
- Extract shared helpers for task matching and block collection
- Replace linear tasks.find() with Map lookups
- Remove mutable module-level counter

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: Box::pin WAC v2 output handler to prevent stack overflow

handle_python_job's async state machine was too large when combined
with handle_wac_v2_output. Box::pin heap-allocates the future.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: merge WAC v1 and v2 task decorators to preserve backward compat

The v2 @task decorator was shadowing the v1 one, breaking WAC v1
scripts that rely on HTTP-based dispatch via /workflow_as_code/ API.

The merged decorator handles three modes:
- v2: inside @workflow context → checkpoint/replay dispatch
- v1: WM_JOB_ID set, no @workflow → HTTP API dispatch + wait_job
- standalone: no Windmill env → execute function body directly

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: skip no_main_func detection for WAC v2 scripts in TS and Python parsers

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: prevent empty/noop dispatch causing infinite requeue loop

- Validate steps.len() > 0 in WAC dispatch handler (issue 3)
- Replace noop StepSuspend throw with never-resolving promise so it
  can't reach the backend as an empty dispatch (issue 4)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: Python task wrapper now converts positional args to kwargs in v2 mode

Previously only **kwargs were passed to _next_step(), silently dropping
positional arguments. Extract shared _merge_args() helper used by both
v1 and v2 paths.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: replace unwrap() with proper error propagation in WAC arg serialization

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: add workspace_id filter to v2_job queries in WAC dispatch

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: prevent race condition in WAC child dispatch

Restructure dispatch to save checkpoint + suspend parent + seed child
checkpoints in a single transaction BEFORE pushing child jobs. This
ensures a fast child can't complete before the parent is suspended.

Also wrap InlineCheckpoint save + running reset in a transaction to
prevent corrupted state on crash.

Use ULID for pre-generated child job IDs (consistent with rest of API).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: include step key and child job ID in WAC error propagation

Move step_key lookup before the success check so failed child errors
include which task failed, the child job ID, and the original error.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* docs: document WAC determinism contract and step dispatch semantics

- Document that workflow functions must be deterministic across replays
- Document that WacStepDispatch.script/args are metadata, not dispatch targets
- Add comments on counter-based key allocation

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: tighten WAC v2 detection to reduce false positives

Replace naive substring matching with line-aware checks that skip
comments and look for specific patterns:
- TS: import from "windmill-client" containing workflow/task
- Python: @workflow and @task decorators with wmill import

Extracted shared helpers in wac_executor.rs used by both executors.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: show failed steps in WacGraph when workflow completes with errors

When flowDone is true and a pending step isn't in completedSteps,
mark it as 'failed' instead of 'running'. The failed state CSS and
XCircle icon were already defined but never triggered.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: unsuspend and fail parent when WAC child push fails

Previously if a child push failed mid-batch, the parent remained
suspended with suspend = num_steps but fewer children, hanging until
the 14-day timeout. Now the push loop catches errors and unsuspends
the parent before returning the error.

Also adds source hash validation: if the script content changes between
replays, the job fails with a clear error instead of silently feeding
stale checkpoint data into wrong steps.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: clear suspend_until when unsuspending WAC parent

Set suspend_until = NULL alongside suspend = 0 in both the child
failure and all-children-complete paths, so the parent doesn't rely
on subtle pull query invariants to be re-picked-up.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* test: add exhaustive edge case tests for WAC v2 SDK

fix: make TS task wrapper non-async to fix unawaited task flush

The async wrapper caused microtask-based thenable auto-resolution that
fired .then() and threw StepSuspend before _flushPending() could capture
unawaited steps — making the flush mechanism completely broken. Now the
thenable is returned directly without async wrapping. Backward compatible
with v1 (all code paths still return awaitables).

Tests added (59 TS + 66 Python) covering: full sequential lifecycle,
step after parallel, parallel after parallel, conditional on step result,
empty/single-task workflows, 10+ steps, falsy value preservation, inline
steps, mixed step/task, unawaited flush, child mode with parallel,
key determinism, large parallel groups, and complex mixed patterns.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: atomic checkpoint updates to prevent parallel child race condition

Replace read-modify-write pattern in handle_wac_child_completion with
atomic SQL operations:
- completed_steps merged via jsonb_set(... || jsonb_build_object(...))
  so concurrent children on different workers don't overwrite each other
- suspend counter decremented atomically with RETURNING to determine
  "all done" condition (instead of checking completed_steps in memory)
- suspend_until cleared in the same atomic decrement statement

Before this fix, two parallel children completing simultaneously could
both load the same checkpoint, each add their step, and save — the
second write would overwrite the first, silently losing a child result
and leaving the parent suspended forever.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: cancel already-pushed children on partial WAC dispatch failure

When pushing child jobs sequentially, if pushing child N fails, children
1..N-1 are already running. Previously the error handler only unsuspended
the parent, leaving orphaned children that would complete and corrupt the
checkpoint state (decrementing suspend on an already-unsuspended parent,
potentially causing duplicate step execution on re-run).

Now on partial failure:
1. Cancel all already-pushed children (prevents them from completing
   and corrupting checkpoint state)
2. Clear pending_steps from checkpoint (so parent doesn't think
   children are outstanding on re-run)
3. Then unsuspend parent (so the error propagates)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: skip WAC duration write and child check for non-WAC parents

The duration write to workflow_as_code_status was running for every
non-flow child with a parent (error handlers, success handlers,
run_script children), even though it was only intended for WAC jobs.

Add WHERE workflow_as_code_status IS NOT NULL to skip non-WAC parents
entirely. Piggyback RETURNING pending_steps.job_ids on the same query
so WAC v2 child completion needs zero extra DB round-trips on the
success path.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: seed child checkpoint in same transaction as push

The child checkpoint insert was happening before the child job was
pushed, violating the FK constraint on v2_job_status. Move it into
the push transaction so the job row exists and the child can't be
picked up before its checkpoint is ready.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: set running=false when WAC parent suspends for child dispatch

The parent job kept running=true after suspending, so workers wouldn't
pick it up when children completed and suspend reached 0. The parent
only advanced when the zombie job detector reset it (~90s). Now the
dispatch suspend sets running=false so the parent is immediately
eligible for pickup.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: WAC parent suspend/unsuspend lifecycle

Keep running=true when suspending the parent so the normal pull query
(WHERE running=false) never picks it up. Keep suspend_until non-null
when decrementing suspend to 0 so the suspended pull query
(WHERE suspend_until IS NOT NULL AND suspend<=0) picks it up.

Previously: setting running=false caused infinite restart loops because
the normal pull query has no suspend check and would immediately re-pick
the parent. Clearing suspend_until on the last child prevented the
suspended pull from ever seeing it, requiring the 90s zombie detector.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: add approval primitive, flow child completion, timeline fixes for WAC v2

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: add error propagation, task options, sleep, and parallel for WAC v2

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* test: fix python SDK tests to use name-based keys and add new test coverage

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: address WAC v2 review findings (sleep timing, error marker, atomicity)

- Fix sleep using suspend=1 instead of 0 to enforce actual delay
- Add approval/sleep resume injection to Python executor
- Fix TS SDK concurrency_limit mapping (was reading wrong property)
- Namespace error marker as __wmill_error to avoid user data collision
- Wrap child completion SQL in transaction for atomicity
- Decrement suspend even when step key is missing (prevents hang)
- Expand TASK_RE to handle export const, let, var, generics
- Validate step key uniqueness before dispatch
- Log warning on checkpoint deserialization failure
- Remove unimplemented delete_after_use from SDKs
- Add TaskError exception class to Python SDK with diagnostic context
- Fix extra positional args handling and add functools.wraps
- Improve getParamNames to handle typed/destructured params

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* sqlx

* sqlx

* test: add WAC v1 e2e integration tests for TS and Python

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: revert fake test versions in typescript-client

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* refactor: remove unused WacGraph component and strip wacToFlow to isWorkflowAsCode

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* refactor: extract shared approval/sleep resume logic into wac_executor

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-09 19:39:24 +00:00

575 lines
20 KiB
Rust

use std::collections::HashMap;
use futures::future::BoxFuture;
use futures::{FutureExt, StreamExt};
use reqwest::Client;
use serde_json::{json, value::RawValue, Value};
use windmill_common::client::AuthedClient;
use windmill_common::error::to_anyhow;
use windmill_common::worker::{Connection, SqlResultCollectionStrategy};
use windmill_common::{error::Error, worker::to_raw_value};
use windmill_object_store::convert_json_line_stream;
use windmill_parser_sql::{
parse_bigquery_sig, parse_db_resource, parse_s3_mode, parse_sql_blocks,
parse_sql_statement_named_params,
};
use windmill_queue::CanceledBy;
use serde::Deserialize;
use crate::common::{build_args_values, resolve_job_timeout};
use crate::common::{
build_http_client, get_reserved_variables, s3_mode_args_to_worker_data, OccupancyMetrics,
S3ModeWorkerData,
};
use crate::handle_child::run_future_with_polling_update_job_poller;
use crate::sanitized_sql_params::sanitize_and_interpolate_unsafe_sql_args;
use gcp_auth::{AuthenticationManager, CustomServiceAccount};
#[allow(non_snake_case)]
#[derive(Deserialize)]
struct BigqueryResponse {
rows: Option<Vec<BigqueryResponseRow>>,
totalRows: Option<Value>,
schema: Option<BigqueryResponseSchema>,
jobComplete: bool,
pageToken: Option<String>,
jobReference: Option<BigQueryResponseJobReference>,
}
#[allow(non_snake_case)]
#[derive(Deserialize, Clone)]
struct BigQueryResponseJobReference {
jobId: String,
projectId: String,
location: Option<String>,
}
#[derive(Deserialize)]
struct BigqueryResponseRow {
f: Vec<BigqueryResponseValue>,
}
#[derive(Deserialize)]
struct BigqueryResponseValue {
v: Value,
}
#[derive(Deserialize)]
struct BigqueryResponseSchema {
fields: Vec<BigqueryResponseSchemaField>,
}
#[derive(Deserialize)]
struct BigqueryResponseSchemaField {
name: String,
r#type: String,
fields: Option<Vec<BigqueryResponseSchemaField>>,
}
#[derive(Deserialize)]
struct BigqueryErrorResponse {
error: BigqueryError,
}
#[derive(Deserialize)]
struct BigqueryError {
message: String,
}
fn do_bigquery_inner<'a>(
query: &'a str,
all_statement_values: &'a HashMap<String, Value>,
project_id: &'a str,
token: &'a str,
timeout_ms: u64,
column_order: Option<&'a mut Option<Vec<String>>>,
skip_collect: bool,
first_row_only: bool,
http_client: &'a Client,
s3: Option<S3ModeWorkerData>,
) -> windmill_common::error::Result<BoxFuture<'a, windmill_common::error::Result<Vec<Box<RawValue>>>>>
{
let param_names = parse_sql_statement_named_params(query, '@');
let statement_values = all_statement_values
.iter()
.filter_map(|(name, val)| {
if param_names.contains(name) {
Some(val)
} else {
None
}
})
.collect::<Vec<&Value>>();
let result_f = async move {
let response = http_client
.post(
"https://bigquery.googleapis.com/bigquery/v2/projects/".to_string()
+ project_id
+ "/queries",
)
.bearer_auth(token)
.json(&json!({
"query": query,
"useLegacySql": false,
"maxResults": if first_row_only { 1 } else { 10000 },
"timeoutMs": timeout_ms,
"queryParameters": statement_values,
}))
.send()
.await
.map_err(|e| {
Error::ExecutionErr(format!("Could not send query to BigQuery API: {}", e))
})?;
match response.error_for_status_ref() {
Ok(_) => {
if skip_collect {
return Ok(vec![]);
} else {
let result = response.json::<BigqueryResponse>().await.map_err(|e| {
Error::ExecutionErr(format!(
"BigQuery API response could not be parsed: {}",
e.to_string()
))
})?;
let rows = handle_bigquery_response(&result, &s3, column_order).await?;
if let Some(s3) = s3 {
let cloned_s3 = s3.clone();
let cloned_http_client = http_client.clone();
let cloned_token = token.to_string();
let rows_stream = async_stream::stream! {
for row in rows.iter() {
yield Ok::<_, windmill_common::error::Error>(row.clone());
}
let mut next_page_token = result.pageToken;
let Some(job_reference) = result.jobReference.clone() else {
return;
};
while let Some(ref next_page_token_value) = next_page_token {
let response2 = cloned_http_client
.get(
format!("https://bigquery.googleapis.com/bigquery/v2/projects/{}/queries/{}", job_reference.projectId, job_reference.jobId),
)
.bearer_auth(cloned_token.as_str())
.query(&[
("pageToken", next_page_token_value.as_str()),
("maxResults", "10000"),
("timeoutMs", timeout_ms.to_string().as_str()),
("location", job_reference.location.as_ref().unwrap_or(&"US".to_string()).as_str()),
])
.send()
.await
.map_err(|e| {
Error::ExecutionErr(format!("Could not send query to BigQuery API: {}", e))
})?;
if let Err(e) = response2.error_for_status_ref() {
match response2.json::<BigqueryErrorResponse>().await {
Ok(bq_err) => {
yield Err(Error::ExecutionErr(format!(
"Error from BigQuery API: {}",
bq_err.error.message
)))
.map_err(to_anyhow)?;
return;
},
Err(_) => {
yield Err(Error::ExecutionErr(format!(
"Error from BigQuery API could not be parsed: {}",
e.to_string()
)))
.map_err(to_anyhow)?;
return;
},
}
}
let result2 = response2.json::<BigqueryResponse>().await.map_err(|e| {
Error::ExecutionErr(format!(
"BigQuery API response could not be parsed: {}",
e.to_string()
))
})?;
let rows = handle_bigquery_response(&result2, &Some(cloned_s3.clone()), None).await?;
for row in rows.into_iter() {
yield Ok::<_, windmill_common::error::Error>(row);
}
next_page_token = result2.pageToken;
}
};
let stream =
convert_json_line_stream(rows_stream.boxed(), s3.format).await?;
s3.upload(stream.boxed()).await?;
return Ok(vec![to_raw_value(&s3.to_return_s3_obj())]);
}
Ok(rows.iter().map(to_raw_value).collect::<Vec<_>>())
}
}
Err(e) => match response.json::<BigqueryErrorResponse>().await {
Ok(bq_err) => Err(Error::ExecutionErr(format!(
"Error from BigQuery API: {}",
bq_err.error.message
)))
.map_err(to_anyhow)?,
Err(_) => Err(Error::ExecutionErr(format!(
"Error from BigQuery API could not be parsed: {}",
e.to_string()
)))
.map_err(to_anyhow)?,
},
}
};
Ok(result_f.boxed())
}
async fn handle_bigquery_response<'a>(
result: &BigqueryResponse,
s3: &Option<S3ModeWorkerData>,
column_order: Option<&'a mut Option<Vec<String>>>,
) -> windmill_common::error::Result<Vec<Value>> {
if !result.jobComplete {
return Err(Error::ExecutionErr(
"BigQuery API did not answer query in time".to_string(),
));
}
if result.rows.is_none() || result.rows.as_ref().unwrap().len() == 0 {
return Ok(serde_json::from_str("[]").unwrap());
}
if result.schema.is_none() {
return Err(Error::ExecutionErr(
"Incomplete response from BigQuery API".to_string(),
));
}
if s3.is_none()
&& result
.totalRows
.as_ref()
.unwrap_or(&json!(""))
.as_str()
.unwrap_or("")
.parse::<i64>()
.unwrap_or(0)
> 10000
{
return Err(Error::ExecutionErr(
"More than 10000 rows were requested, use LIMIT 10000 to limit the number of rows or use S3 streaming for larger datasets: https://windmill.dev/docs/core_concepts/sql_to_s3_streaming"
.to_string(),
));
}
if let Some(column_order) = column_order {
*column_order = Some(
result
.schema
.as_ref()
.unwrap()
.fields
.iter()
.map(|x| x.name.clone())
.collect::<Vec<String>>(),
);
}
let rows = result
.rows
.as_ref()
.unwrap()
.iter()
.map(|row| {
let mut row_map = serde_json::Map::new();
row.f
.iter()
.zip(result.schema.as_ref().unwrap().fields.iter())
.for_each(|(field, schema)| {
row_map.insert(
schema.name.clone(),
parse_val(&field.v, &schema.r#type, &schema),
);
});
Value::from(row_map)
})
.collect::<Vec<_>>();
Ok(rows)
}
use windmill_queue::MiniPulledJob;
pub async fn do_bigquery(
job: &MiniPulledJob,
client: &AuthedClient,
query: &str,
conn: &Connection,
mem_peak: &mut i32,
canceled_by: &mut Option<CanceledBy>,
worker_name: &str,
column_order: &mut Option<Vec<String>>,
occupancy_metrics: &mut OccupancyMetrics,
parent_runnable_path: Option<String>,
) -> windmill_common::error::Result<Box<RawValue>> {
let bigquery_args = build_args_values(job, client, conn).await?;
let inline_db_res_path = parse_db_resource(&query);
let s3 = parse_s3_mode(&query)?.map(|s3| s3_mode_args_to_worker_data(s3, client.clone(), job));
let db_arg = if let Some(inline_db_res_path) = inline_db_res_path {
Some(
client
.get_resource_value_interpolated::<serde_json::Value>(
&inline_db_res_path,
Some(job.id.to_string()),
)
.await?,
)
} else {
bigquery_args.get("database").cloned()
};
let database = if let Some(db) = db_arg {
db.to_string()
} else {
return Err(Error::BadRequest("Missing database argument".to_string()));
};
let annotations = windmill_common::worker::SqlAnnotations::parse(query);
let collection_strategy = if annotations.return_last_result {
SqlResultCollectionStrategy::LastStatementAllRows
} else {
annotations.result_collection
};
let service_account = CustomServiceAccount::from_json(&database)
.map_err(|e| Error::ExecutionErr(e.to_string()))?;
let authentication_manager = AuthenticationManager::from(service_account);
let scopes = &["https://www.googleapis.com/auth/bigquery"];
let token = authentication_manager
.get_token(scopes)
.await
.map_err(|e| Error::ExecutionErr(e.to_string()))?;
let (timeout_duration, _, _) =
resolve_job_timeout(&conn, &job.workspace_id, job.id, job.timeout).await;
let timeout_ms = timeout_duration.as_millis() as u64;
let http_client = build_http_client(timeout_duration)?;
let project_id = authentication_manager
.project_id()
.await
.map_err(|e| Error::ExecutionErr(e.to_string()))?;
let sig = parse_bigquery_sig(&query)
.map_err(|x| Error::ExecutionErr(x.to_string()))?
.args;
let reserved_variables =
get_reserved_variables(job, &client.token, conn, parent_runnable_path).await?;
let (query, args_to_skip) = &sanitize_and_interpolate_unsafe_sql_args(
query,
&sig,
&bigquery_args,
&reserved_variables,
)?;
let queries = parse_sql_blocks(query);
let mut statement_values: HashMap<String, Value> = HashMap::new();
for arg in &sig {
if args_to_skip.contains(&arg.name) {
continue;
}
let arg_t = arg.otyp.clone().unwrap_or_else(|| "string".to_string());
let arg_n = arg.clone().name;
let arg_v = bigquery_args.get(&arg.name).cloned().unwrap_or(json!(""));
let bigquery_v = if arg_t.ends_with("[]") {
let base_type = arg_t.strip_suffix("[]").unwrap_or(&arg_t);
json!({
"name": arg.name,
"parameterType": {
"type": "ARRAY",
"arrayType": {
"type": base_type.to_uppercase()
}
},
"parameterValue": {
"arrayValues": bigquery_args
.get(&arg.name)
.unwrap_or(&json!([]))
.as_array()
.unwrap_or(&vec![])
.iter()
.map(|x| {
convert_val(base_type.to_string(), x.clone())
})
.collect::<Vec<Value>>()
}
})
} else {
json!({
"name": arg_n,
"parameterType": {
"type": arg_t.to_uppercase()
},
"parameterValue": {
"value": convert_val(arg_t, arg_v),
}
})
};
statement_values.insert(arg_n, bigquery_v);
}
let result_f = async move {
let mut results = vec![];
for (i, q) in queries.iter().enumerate() {
let result = do_bigquery_inner(
q,
&statement_values,
&project_id,
token.as_str(),
timeout_ms,
if i == queries.len() - 1
&& s3.is_none()
&& collection_strategy.collect_last_statement_only(queries.len())
&& !collection_strategy.collect_scalar()
{
Some(column_order)
} else {
None
},
collection_strategy.collect_last_statement_only(queries.len())
&& i < queries.len() - 1,
collection_strategy.collect_first_row_only(),
&http_client,
s3.clone(),
)?
.await?;
results.push(result);
}
collection_strategy.collect(results)
};
let r = run_future_with_polling_update_job_poller(
job.id,
job.timeout,
conn,
mem_peak,
canceled_by,
result_f,
worker_name,
&job.workspace_id,
&mut Some(occupancy_metrics),
Box::pin(futures::stream::once(async { 0 })),
)
.await?;
*mem_peak = (r.get().len() / 1000) as i32;
Ok(r)
}
fn convert_val(arg_t: String, arg_v: Value) -> Value {
match arg_t.as_str() {
"timestamp" | "datetime" | "date" | "time" => {
let mut v: String = arg_v.as_str().unwrap_or("").to_owned();
match arg_t.as_str() {
"timestamp" | "datetime" => {
v = v.trim_end_matches("Z").to_string();
}
"date" => {
let arr = v.split("T").collect::<Vec<&str>>();
match arr.as_slice() {
[date, _] => {
v = date.to_string();
}
_ => {}
}
}
"time" => {
let arr = v.split("T").collect::<Vec<&str>>();
match arr.as_slice() {
[_, time] => {
v = time.trim_end_matches("Z").to_string();
}
_ => {}
}
}
_ => {}
}
json!({ "value": json!(v) })
}
_ => {
let mut v = arg_v;
if !v.is_string() {
// if not string, convert to string for api request
v = json!(v.to_string());
}
json!({
"value": v,
}
)
}
}
}
fn parse_val(value: &Value, typ: &str, schema: &BigqueryResponseSchemaField) -> Value {
let str_value = value.as_str().unwrap_or("").to_string();
if value.is_array() {
return Value::Array(
value
.as_array()
.unwrap_or(&vec![])
.iter()
.map(|x| {
parse_val(
&serde_json::from_value::<BigqueryResponseValue>(x.clone())
.ok()
.unwrap_or(BigqueryResponseValue { v: json!({}) })
.v,
typ,
schema,
)
})
.collect::<Vec<Value>>(),
);
}
match typ.to_lowercase().as_str() {
"struct" | "record" => {
let mut nested_row_map = serde_json::Map::new();
serde_json::from_value::<BigqueryResponseRow>(value.clone())
.ok()
.unwrap_or(BigqueryResponseRow { f: vec![] })
.f
.iter()
.zip(schema.fields.as_ref().clone().unwrap_or(&vec![]).iter())
.for_each(|(f, s)| {
nested_row_map.insert(s.name.clone(), parse_val(&f.v, &s.r#type, &s));
});
Value::from(nested_row_map)
}
"bool" | "boolean" => json!(str_value.parse::<bool>().ok().unwrap_or(false)),
"float" | "float64" => json!(str_value.parse::<f64>().ok().unwrap_or(0.0)),
"int64" | "integer" | "timestamp" => json!(str_value.parse::<i64>().ok().unwrap_or(0)),
"json" => serde_json::from_str(&str_value).ok().unwrap_or(json!({})),
_ => value.clone(),
}
}