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https://github.com/GreptimeTeam/greptimedb.git
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chore: upgrade rust toolchain to latest nightly (#2049)
* chore: upgrade rust toolchain to latest nightly * rebase develop * update rust toolchain in ci
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@@ -654,7 +654,7 @@ pub(crate) mod greptime_builtin {
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) -> PyResult<PyObjectRef> {
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let percent =
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expressions::Literal::new(datafusion_common::ScalarValue::Float64(Some(percent)));
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return eval_aggr_fn(
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eval_aggr_fn(
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expressions::ApproxPercentileCont::new(
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vec![
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Arc::new(expressions::Column::new("expr0", 0)) as _,
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@@ -666,7 +666,7 @@ pub(crate) mod greptime_builtin {
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.map_err(|err| from_df_err(err, vm))?,
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&[values.to_arrow_array()],
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vm,
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);
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)
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}
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/// effectively equals to `list(vector)`
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@@ -857,7 +857,7 @@ pub(crate) mod greptime_builtin {
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// pyfunction can return PyResult<...>, args can be like PyObjectRef or anything
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// impl IntoPyNativeFunc, see rustpython-vm function for more details
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let args = vec![base.as_vector_ref(), arg_pow];
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let res = PowFunction::default()
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let res = PowFunction
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.eval(FunctionContext::default(), &args)
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.map_err(|err| {
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vm.new_runtime_error(format!(
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@@ -14,8 +14,8 @@
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use std::cell::RefCell;
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use std::collections::{HashMap, HashSet};
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use std::rc::Rc;
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use std::result::Result as StdResult;
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use std::sync::Arc;
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use common_recordbatch::RecordBatch;
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use common_telemetry::{info, timer};
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@@ -37,7 +37,7 @@ use crate::python::rspython::dataframe_impl::data_frame::set_dataframe_in_scope;
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use crate::python::rspython::dataframe_impl::init_data_frame;
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use crate::python::rspython::utils::{format_py_error, is_instance, py_obj_to_vec};
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thread_local!(static INTERPRETER: RefCell<Option<Arc<Interpreter>>> = RefCell::new(None));
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thread_local!(static INTERPRETER: RefCell<Option<Rc<Interpreter>>> = RefCell::new(None));
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/// Using `RustPython` to run a parsed `Coprocessor` struct as input to execute python code
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pub(crate) fn rspy_exec_parsed(
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@@ -48,7 +48,7 @@ pub(crate) fn rspy_exec_parsed(
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let _t = timer!(metric::METRIC_RSPY_EXEC_TOTAL_ELAPSED);
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// 3. get args from `rb`, and cast them into PyVector
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let args: Vec<PyVector> = if let Some(rb) = rb {
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let arg_names = copr.deco_args.arg_names.clone().unwrap_or(vec![]);
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let arg_names = copr.deco_args.arg_names.clone().unwrap_or_default();
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let args = select_from_rb(rb, &arg_names)?;
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check_args_anno_real_type(&arg_names, &args, copr, rb)?;
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args
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@@ -99,7 +99,7 @@ pub(crate) fn exec_with_cached_vm(
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rb: &Option<RecordBatch>,
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args: Vec<PyVector>,
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params: &HashMap<String, String>,
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vm: &Arc<Interpreter>,
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vm: &Rc<Interpreter>,
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) -> Result<RecordBatch> {
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vm.enter(|vm| -> Result<RecordBatch> {
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let _t = timer!(metric::METRIC_RSPY_EXEC_ELAPSED);
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@@ -188,7 +188,7 @@ fn try_into_columns(
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}
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/// init interpreter with type PyVector and Module: greptime
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pub(crate) fn init_interpreter() -> Arc<Interpreter> {
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pub(crate) fn init_interpreter() -> Rc<Interpreter> {
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let _t = timer!(metric::METRIC_RSPY_INIT_ELAPSED);
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INTERPRETER.with(|i| {
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i.borrow_mut()
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@@ -202,7 +202,7 @@ pub(crate) fn init_interpreter() -> Arc<Interpreter> {
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let mut settings = vm::Settings::default();
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// disable SIG_INT handler so our own binary can take ctrl_c handler
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settings.no_sig_int = true;
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let interpreter = Arc::new(vm::Interpreter::with_init(settings, |vm| {
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let interpreter = Rc::new(vm::Interpreter::with_init(settings, |vm| {
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// not using full stdlib to prevent security issue, instead filter out a few simple util module
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vm.add_native_modules(
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rustpython_stdlib::get_module_inits()
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@@ -136,8 +136,8 @@ pub fn py_obj_to_vec(
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match columnar_value {
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DFColValue::Scalar(ScalarValue::List(scalars, _datatype)) => match scalars {
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Some(scalars) => {
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let array = ScalarValue::iter_to_array(scalars.into_iter())
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.context(error::DataFusionSnafu)?;
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let array =
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ScalarValue::iter_to_array(scalars).context(error::DataFusionSnafu)?;
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Helper::try_into_vector(array).context(error::TypeCastSnafu)
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}
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