From 9f60b9cdf8a07f0b395c60f521d00498061240bb Mon Sep 17 00:00:00 2001 From: Sandy Spicer Date: Fri, 11 Oct 2024 13:37:04 -0700 Subject: [PATCH] feat: rust udf trends (#25503) Co-authored-by: github-actions <41898282+github-actions[bot]@users.noreply.github.com> --- docker/clickhouse/user_defined_function.xml | 26 +- funnel-udf/src/main.rs | 252 +----------------- funnel-udf/src/steps.rs | 248 +++++++++++++++++ funnel-udf/src/trends.rs | 193 ++++++++++++++ posthog/hogql/functions/mapping.py | 2 +- .../insights/funnels/funnel_trends_udf.py | 6 +- .../insights/funnels/funnel_udf.py | 33 +-- .../test_funnel_correlation_actors_udf.ambr | 15 +- .../test_funnel_strict_persons_udf.ambr | 9 +- .../__snapshots__/test_funnel_strict_udf.ambr | 18 +- .../__snapshots__/test_funnel_trends_udf.ambr | 15 +- .../funnels/test/test_funnel_strict_udf.py | 53 +++- .../funnels/test/test_funnel_trends.py | 44 +-- .../funnels/test/test_funnel_trends_udf.py | 124 ++++++++- posthog/user_scripts/aggregate_funnel | 4 +- posthog/user_scripts/aggregate_funnel_aarch64 | Bin 574720 -> 627216 bytes .../aggregate_funnel_array_trends_test.py | 4 +- .../user_scripts/aggregate_funnel_trends.py | 25 +- posthog/user_scripts/aggregate_funnel_x86_64 | Bin 580240 -> 637856 bytes .../latest_user_defined_function.xml | 54 ++-- posthog/user_scripts/v0/aggregate_funnel | 4 +- .../user_scripts/v0/aggregate_funnel_aarch64 | Bin 574720 -> 627216 bytes .../v0/aggregate_funnel_array_trends_test.py | 4 +- .../v0/aggregate_funnel_trends.py | 25 +- .../user_scripts/v0/aggregate_funnel_x86_64 | Bin 580240 -> 637856 bytes .../user_scripts/v0/user_defined_function.xml | 54 ++-- 26 files changed, 810 insertions(+), 402 deletions(-) create mode 100644 funnel-udf/src/steps.rs create mode 100644 funnel-udf/src/trends.rs diff --git a/docker/clickhouse/user_defined_function.xml b/docker/clickhouse/user_defined_function.xml index 6af0f89bdafdb..b8fac26d1887c 100644 --- a/docker/clickhouse/user_defined_function.xml +++ b/docker/clickhouse/user_defined_function.xml @@ -29,7 +29,7 @@ value JSONEachRow - aggregate_funnel + aggregate_funnel steps 600 @@ -63,7 +63,7 @@ value JSONEachRow - aggregate_funnel + aggregate_funnel steps 600 @@ -97,7 +97,7 @@ value JSONEachRow - aggregate_funnel + aggregate_funnel steps 600 @@ -138,7 +138,7 @@ executable_pool aggregate_funnel_trends - Array(Tuple(DateTime, Int8, Nullable(String))) + Array(Tuple(UInt64, Int8, Nullable(String))) result UInt8 @@ -169,11 +169,11 @@ prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), Nullable(String), Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, Nullable(String), Array(Int8))) value JSONEachRow - aggregate_funnel_trends.py + aggregate_funnel trends 600 @@ -181,7 +181,7 @@ executable_pool aggregate_funnel_array_trends - Array(Tuple(DateTime, Int8, Array(String))) + Array(Tuple(UInt64, Int8, Array(String))) result UInt8 @@ -208,11 +208,11 @@ prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), Array(String), Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, Array(String), Array(Int8))) value JSONEachRow - aggregate_funnel_array_trends.py + aggregate_funnel trends 600 @@ -220,7 +220,7 @@ executable_pool aggregate_funnel_cohort_trends - Array(Tuple(DateTime, Int8, UInt64)) + Array(Tuple(UInt64, Int8, UInt64)) result UInt8 @@ -247,11 +247,11 @@ prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), UInt64, Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, UInt64, Array(Int8))) value JSONEachRow - aggregate_funnel_cohort_trends.py + aggregate_funnel trends 600 @@ -285,7 +285,7 @@ prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), Array(String), Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, Array(String), Array(Int8))) value JSONEachRow diff --git a/funnel-udf/src/main.rs b/funnel-udf/src/main.rs index 6169b0de2f824..ec45afdad2f58 100644 --- a/funnel-udf/src/main.rs +++ b/funnel-udf/src/main.rs @@ -1,9 +1,9 @@ +mod steps; +mod trends; + +use std::env; use serde::{Deserialize, Serialize}; -use serde_json::json; use std::io::{self, BufRead, Write}; -use std::iter::repeat; -use itertools::{Itertools}; -use uuid::Uuid; #[derive(Clone, PartialEq, Deserialize, Serialize)] #[serde(untagged)] @@ -13,251 +13,19 @@ enum PropVal { Int(u32), } -#[derive(Clone, Deserialize)] -struct EnteredTimestamp { - timestamp: f64, - timings: Vec, - uuids: Vec, -} - -#[derive(Clone, Deserialize)] -struct Event { - timestamp: f64, - uuid: Uuid, - breakdown: PropVal, - steps: Vec, -} - -#[derive(Deserialize)] -struct Args { - num_steps: usize, - conversion_window_limit: u64, // In seconds - breakdown_attribution_type: String, - funnel_order_type: String, - prop_vals: Vec, - value: Vec, -} - -#[derive(Serialize)] -struct Result(i8, PropVal, Vec, Vec>); - -struct Vars { - max_step: (usize, EnteredTimestamp), - event_uuids: Vec>, - entered_timestamp: Vec -} - -struct AggregateFunnelRow { - breakdown_step: Option, - results: Vec, -} - -const MAX_REPLAY_EVENTS: usize = 10; - -const DEFAULT_ENTERED_TIMESTAMP: EnteredTimestamp = EnteredTimestamp { - timestamp: 0.0, - timings: vec![], - uuids: vec![], -}; - -#[inline(always)] -fn parse_args(line: &str) -> Args { - serde_json::from_str(line).expect("Invalid JSON input") -} - -impl AggregateFunnelRow { - #[inline(always)] - fn calculate_funnel_from_user_events(&mut self, args: &Args) -> &Vec { - if args.breakdown_attribution_type.starts_with("step_") { - self.breakdown_step = args.breakdown_attribution_type[5..].parse::().ok() - } - - args.prop_vals.iter().for_each(|prop_val| self.loop_prop_val(args, prop_val)); - - &self.results - } - - #[inline(always)] - fn loop_prop_val(&mut self, args: &Args, prop_val: &PropVal) { - let mut vars = Vars { - max_step: (0, DEFAULT_ENTERED_TIMESTAMP.clone()), - event_uuids: repeat(Vec::new()).take(args.num_steps).collect(), - entered_timestamp: vec![DEFAULT_ENTERED_TIMESTAMP.clone(); args.num_steps + 1] - }; - - let filtered_events = args.value.iter() - .filter(|e| { - if args.breakdown_attribution_type == "all_events" { - e.breakdown == *prop_val - } else { - true - } - }) - .group_by(|e| e.timestamp); - - for (timestamp, events_with_same_timestamp) in &filtered_events { - let events_with_same_timestamp: Vec<_> = events_with_same_timestamp.collect(); - vars.entered_timestamp[0] = EnteredTimestamp { - timestamp, - timings: vec![], - uuids: vec![], - }; - - if events_with_same_timestamp.len() == 1 { - if !self.process_event( - args, - &mut vars, - &events_with_same_timestamp[0], - prop_val, - false - ) { - return; - } - } else if events_with_same_timestamp.iter().map(|x| &x.steps).all_equal() { - // Deal with the most common case where they are all the same event (order doesn't matter) - for event in events_with_same_timestamp { - if !self.process_event( - args, - &mut vars, - event, - prop_val, - false - ) { - return; - } - } - } else { - // Handle permutations for different events with the same timestamp - // We ignore strict steps and exclusions in this case - // The behavior here is mostly dictated by how it was handled in the old style - - let sorted_events = events_with_same_timestamp - .iter() - .flat_map(|&event| { - event.steps - .iter() - .filter(|&&step| step > 0) - .map(|&step| Event { steps: vec![step], ..event.clone() }) - }).sorted_by_key(|event| event.steps[0]); - - // Run exclusions, if they exist, then run matching events. - for event in sorted_events { - if !self.process_event( - args, - &mut vars, - &event, - &prop_val, - true - ) { - return; - } - } - } - - // If we hit the goal, we can terminate early - if vars.entered_timestamp[args.num_steps].timestamp > 0.0 { - break; - } - } - - // Find the furthest step we have made it to and print it - let final_index = vars.max_step.0; - let final_value = &vars.max_step.1; - - for i in 0..final_index { - //if event_uuids[i].len() >= MAX_REPLAY_EVENTS && !event_uuids[i].contains(&final_value.uuids[i]) { - // Always put the actual event uuids first, we use it to extract timestamps - // This might create duplicates, but that's fine (we can remove it in clickhouse) - vars.event_uuids[i].insert(0, final_value.uuids[i].clone()); - } - self.results.push(Result( - final_index as i8 - 1, - prop_val.clone(), - final_value.timings.windows(2).map(|w| w[1] - w[0]).collect(), - vars.event_uuids, - )) - } - - #[inline(always)] - fn process_event( - &mut self, - args: &Args, - vars: &mut Vars, - event: &Event, - prop_val: &PropVal, - processing_multiple_events: bool - ) -> bool { - for step in event.steps.iter().rev() { - let mut exclusion = false; - let step = (if *step < 0 { - exclusion = true; - -*step - } else { - *step - }) as usize; - - let in_match_window = (event.timestamp - vars.entered_timestamp[step - 1].timestamp) <= args.conversion_window_limit as f64; - let already_reached_this_step = vars.entered_timestamp[step].timestamp == vars.entered_timestamp[step - 1].timestamp - && vars.entered_timestamp[step].timestamp != 0.0; - - if in_match_window && !already_reached_this_step { - if exclusion { - self.results.push(Result(-1, prop_val.clone(), vec![], vec![])); - return false; - } - let is_unmatched_step_attribution = self.breakdown_step.map(|breakdown_step| step == breakdown_step - 1).unwrap_or(false) && *prop_val != event.breakdown; - let already_used_event = processing_multiple_events && vars.entered_timestamp[step-1].uuids.contains(&event.uuid); - if !is_unmatched_step_attribution && !already_used_event { - vars.entered_timestamp[step] = EnteredTimestamp { - timestamp: vars.entered_timestamp[step - 1].timestamp, - timings: { - let mut timings = vars.entered_timestamp[step - 1].timings.clone(); - timings.push(event.timestamp); - timings - }, - uuids: { - let mut uuids = vars.entered_timestamp[step - 1].uuids.clone(); - uuids.push(event.uuid); - uuids - }, - }; - if vars.event_uuids[step - 1].len() < MAX_REPLAY_EVENTS - 1 { - vars.event_uuids[step - 1].push(event.uuid); - } - if step > vars.max_step.0 { - vars.max_step = (step, vars.entered_timestamp[step].clone()); - } - } - } - } - - // If a strict funnel, clear all of the steps that we didn't match to - // If we are processing multiple events, skip this step, because ordering makes it complicated - if !processing_multiple_events && args.funnel_order_type == "strict" { - for i in 1..vars.entered_timestamp.len() { - if !event.steps.contains(&(i as i8)) { - vars.entered_timestamp[i] = DEFAULT_ENTERED_TIMESTAMP; - } - } - } - - true - } -} - fn main() { + let args: Vec = env::args().collect(); + let arg = args.get(1).map(|x| x.as_str()); + let stdin = io::stdin(); let mut stdout = io::stdout(); for line in stdin.lock().lines() { if let Ok(line) = line { - let args = parse_args(&line); - let mut aggregate_funnel_row = AggregateFunnelRow { - results: Vec::with_capacity(args.prop_vals.len()), - breakdown_step: Option::None, + let output = match arg { + Some("trends") => trends::process_line(&line), + _ => steps::process_line(&line), }; - let result = aggregate_funnel_row.calculate_funnel_from_user_events(&args); - let output = json!({ "result": result }); writeln!(stdout, "{}", output).unwrap(); stdout.flush().unwrap(); } diff --git a/funnel-udf/src/steps.rs b/funnel-udf/src/steps.rs new file mode 100644 index 0000000000000..a5075ecc4e864 --- /dev/null +++ b/funnel-udf/src/steps.rs @@ -0,0 +1,248 @@ +use std::iter::repeat; +use itertools::Itertools; +use serde::{Deserialize, Serialize}; +use serde_json::{json, Value}; +use uuid::Uuid; +use crate::PropVal; + +#[derive(Clone, Deserialize)] +struct EnteredTimestamp { + timestamp: f64, + timings: Vec, + uuids: Vec, +} + +#[derive(Clone, Deserialize)] +struct Event { + timestamp: f64, + uuid: Uuid, + breakdown: PropVal, + steps: Vec, +} + +#[derive(Deserialize)] +struct Args { + num_steps: usize, + conversion_window_limit: u64, // In seconds + breakdown_attribution_type: String, + funnel_order_type: String, + prop_vals: Vec, + value: Vec, +} + +#[derive(Serialize)] +struct Result(i8, PropVal, Vec, Vec>); + +struct Vars { + max_step: (usize, EnteredTimestamp), + event_uuids: Vec>, + entered_timestamp: Vec +} + +struct AggregateFunnelRow { + breakdown_step: Option, + results: Vec, +} + +const MAX_REPLAY_EVENTS: usize = 10; + +const DEFAULT_ENTERED_TIMESTAMP: EnteredTimestamp = EnteredTimestamp { + timestamp: 0.0, + timings: vec![], + uuids: vec![], +}; + +pub fn process_line(line: &str) -> Value { + let args = parse_args(&line); + let mut aggregate_funnel_row = AggregateFunnelRow { + results: Vec::with_capacity(args.prop_vals.len()), + breakdown_step: Option::None, + }; + let result = aggregate_funnel_row.calculate_funnel_from_user_events(&args); + json!({ "result": result }) +} + +#[inline(always)] +fn parse_args(line: &str) -> Args { + serde_json::from_str(line).expect("Invalid JSON input") +} + +impl AggregateFunnelRow { + #[inline(always)] + fn calculate_funnel_from_user_events(&mut self, args: &Args) -> &Vec { + if args.breakdown_attribution_type.starts_with("step_") { + self.breakdown_step = args.breakdown_attribution_type[5..].parse::().ok() + } + + args.prop_vals.iter().for_each(|prop_val| self.loop_prop_val(args, prop_val)); + + &self.results + } + + #[inline(always)] + fn loop_prop_val(&mut self, args: &Args, prop_val: &PropVal) { + let mut vars = Vars { + max_step: (0, DEFAULT_ENTERED_TIMESTAMP.clone()), + event_uuids: repeat(Vec::new()).take(args.num_steps).collect(), + entered_timestamp: vec![DEFAULT_ENTERED_TIMESTAMP.clone(); args.num_steps + 1] + }; + + let filtered_events = args.value.iter() + .filter(|e| { + if args.breakdown_attribution_type == "all_events" { + e.breakdown == *prop_val + } else { + true + } + }) + .group_by(|e| e.timestamp); + + for (timestamp, events_with_same_timestamp) in &filtered_events { + let events_with_same_timestamp: Vec<_> = events_with_same_timestamp.collect(); + vars.entered_timestamp[0] = EnteredTimestamp { + timestamp, + timings: vec![], + uuids: vec![], + }; + + if events_with_same_timestamp.len() == 1 { + if !self.process_event( + args, + &mut vars, + &events_with_same_timestamp[0], + prop_val, + false + ) { + return; + } + } else if events_with_same_timestamp.iter().map(|x| &x.steps).all_equal() { + // Deal with the most common case where they are all the same event (order doesn't matter) + for event in events_with_same_timestamp { + if !self.process_event( + args, + &mut vars, + event, + prop_val, + false + ) { + return; + } + } + } else { + // Handle permutations for different events with the same timestamp + // We ignore strict steps and exclusions in this case + // The behavior here is mostly dictated by how it was handled in the old style + + let sorted_events = events_with_same_timestamp + .iter() + .flat_map(|&event| { + event.steps + .iter() + .filter(|&&step| step > 0) + .map(|&step| Event { steps: vec![step], ..event.clone() }) + }).sorted_by_key(|event| event.steps[0]); + + // Run exclusions, if they exist, then run matching events. + for event in sorted_events { + if !self.process_event( + args, + &mut vars, + &event, + &prop_val, + true + ) { + return; + } + } + } + + // If we hit the goal, we can terminate early + if vars.entered_timestamp[args.num_steps].timestamp > 0.0 { + break; + } + } + + // Find the furthest step we have made it to and print it + let final_index = vars.max_step.0; + let final_value = &vars.max_step.1; + + for i in 0..final_index { + //if event_uuids[i].len() >= MAX_REPLAY_EVENTS && !event_uuids[i].contains(&final_value.uuids[i]) { + // Always put the actual event uuids first, we use it to extract timestamps + // This might create duplicates, but that's fine (we can remove it in clickhouse) + vars.event_uuids[i].insert(0, final_value.uuids[i].clone()); + } + self.results.push(Result( + final_index as i8 - 1, + prop_val.clone(), + final_value.timings.windows(2).map(|w| w[1] - w[0]).collect(), + vars.event_uuids, + )) + } + + #[inline(always)] + fn process_event( + &mut self, + args: &Args, + vars: &mut Vars, + event: &Event, + prop_val: &PropVal, + processing_multiple_events: bool + ) -> bool { + for step in event.steps.iter().rev() { + let mut exclusion = false; + let step = (if *step < 0 { + exclusion = true; + -*step + } else { + *step + }) as usize; + + let in_match_window = (event.timestamp - vars.entered_timestamp[step - 1].timestamp) <= args.conversion_window_limit as f64; + let already_reached_this_step = vars.entered_timestamp[step].timestamp == vars.entered_timestamp[step - 1].timestamp + && vars.entered_timestamp[step].timestamp != 0.0; + + if in_match_window && !already_reached_this_step { + if exclusion { + self.results.push(Result(-1, prop_val.clone(), vec![], vec![])); + return false; + } + let is_unmatched_step_attribution = self.breakdown_step.map(|breakdown_step| step == breakdown_step - 1).unwrap_or(false) && *prop_val != event.breakdown; + let already_used_event = processing_multiple_events && vars.entered_timestamp[step-1].uuids.contains(&event.uuid); + if !is_unmatched_step_attribution && !already_used_event { + vars.entered_timestamp[step] = EnteredTimestamp { + timestamp: vars.entered_timestamp[step - 1].timestamp, + timings: { + let mut timings = vars.entered_timestamp[step - 1].timings.clone(); + timings.push(event.timestamp); + timings + }, + uuids: { + let mut uuids = vars.entered_timestamp[step - 1].uuids.clone(); + uuids.push(event.uuid); + uuids + }, + }; + if vars.event_uuids[step - 1].len() < MAX_REPLAY_EVENTS - 1 { + vars.event_uuids[step - 1].push(event.uuid); + } + if step > vars.max_step.0 { + vars.max_step = (step, vars.entered_timestamp[step].clone()); + } + } + } + } + + // If a strict funnel, clear all of the steps that we didn't match to + // If we are processing multiple events, skip this step, because ordering makes it complicated + if !processing_multiple_events && args.funnel_order_type == "strict" { + for i in 1..vars.entered_timestamp.len() { + if !event.steps.contains(&(i as i8)) { + vars.entered_timestamp[i] = DEFAULT_ENTERED_TIMESTAMP; + } + } + } + + true + } +} \ No newline at end of file diff --git a/funnel-udf/src/trends.rs b/funnel-udf/src/trends.rs new file mode 100644 index 0000000000000..0b9cdd259e247 --- /dev/null +++ b/funnel-udf/src/trends.rs @@ -0,0 +1,193 @@ +use std::collections::HashMap; +use std::str::FromStr; +use itertools::Itertools; +use serde::{Deserialize, Serialize}; +use serde_json::{json, Value}; +use crate::PropVal; + +fn deserialize_number_from_string<'de, D>(deserializer: D) -> Result +where + D: serde::Deserializer<'de>, +{ + let s = String::deserialize(deserializer)?; + u64::from_str(&s).map_err(serde::de::Error::custom) +} + +#[derive(Clone, Deserialize)] +struct EnteredTimestamp { + timestamp: f64, + timings: Vec, +} + +#[derive(Clone, Deserialize)] +struct Event { + timestamp: f64, + #[serde(deserialize_with = "deserialize_number_from_string")] + interval_start: u64, + breakdown: PropVal, + steps: Vec, +} + +#[derive(Deserialize)] +struct Args { + from_step: usize, + num_steps: usize, + conversion_window_limit: u64, // In seconds + breakdown_attribution_type: String, + funnel_order_type: String, + prop_vals: Vec, + value: Vec, +} + +#[derive(Serialize)] +struct ResultStruct(u64, i8, PropVal); + +struct Vars { + interval_start_to_entered_timestamps: HashMap>, +} + +struct AggregateFunnelRow { + breakdown_step: Option, + results: HashMap, +} + +const DEFAULT_ENTERED_TIMESTAMP: EnteredTimestamp = EnteredTimestamp { + timestamp: 0.0, + timings: vec![], +}; + +pub fn process_line(line: &str) -> Value { + let args = parse_args(&line); + let mut aggregate_funnel_row = AggregateFunnelRow { + results: HashMap::new(), + breakdown_step: Option::None, + }; + aggregate_funnel_row.calculate_funnel_from_user_events(&args); + let result: Vec = aggregate_funnel_row.results.into_values().collect(); + json!({ "result": result }) +} + +#[inline(always)] +fn parse_args(line: &str) -> Args { + serde_json::from_str(line).expect("Invalid JSON input") +} + +impl AggregateFunnelRow { + #[inline(always)] + fn calculate_funnel_from_user_events(&mut self, args: &Args) { + if args.breakdown_attribution_type.starts_with("step_") { + self.breakdown_step = args.breakdown_attribution_type[5..].parse::().ok() + } + + args.prop_vals.iter().for_each(|prop_val| self.loop_prop_val(args, prop_val)); + } + + #[inline(always)] + fn loop_prop_val(&mut self, args: &Args, prop_val: &PropVal) { + let mut vars = Vars { + interval_start_to_entered_timestamps: HashMap::new(), + }; + + let filtered_events = args.value.iter() + .filter(|e| { + if args.breakdown_attribution_type == "all_events" { + e.breakdown == *prop_val + } else { + true + } + }) + .group_by(|e| e.timestamp); + + for (_timestamp, events_with_same_timestamp) in &filtered_events { + let events_with_same_timestamp: Vec<_> = events_with_same_timestamp.collect(); + for event in events_with_same_timestamp { + if !self.process_event( + args, + &mut vars, + &event, + prop_val, + ) { + return + } + } + } + + + // At this point, everything left in entered_timestamps is a failure, if it has made it to from_step + for entered_timestamp in vars.interval_start_to_entered_timestamps.values() { + if !self.results.contains_key(&(entered_timestamp[0].timestamp as u64)) && entered_timestamp[0].timings.len() > 0 { + self.results.insert(entered_timestamp[0].timestamp as u64, ResultStruct(entered_timestamp[0].timestamp as u64, -1, prop_val.clone() )); + } + } + } + + #[inline(always)] + fn process_event( + &mut self, + args: &Args, + vars: &mut Vars, + event: &Event, + prop_val: &PropVal, + ) -> bool { + for step in event.steps.iter().rev() { + let mut exclusion = false; + let step = (if *step < 0 { + exclusion = true; + -*step + } else { + *step + }) as usize; + + if step == 1 { + if !vars.interval_start_to_entered_timestamps.contains_key(&event.interval_start) && !self.results.contains_key(&event.interval_start) { + let mut entered_timestamp = vec![DEFAULT_ENTERED_TIMESTAMP.clone(); args.num_steps + 1]; + entered_timestamp[0] = EnteredTimestamp { timestamp: event.interval_start as f64, timings: if args.from_step == 0 {vec![1.0]} else {vec![]} }; + entered_timestamp[1] = EnteredTimestamp { timestamp: event.timestamp, timings: vec![event.timestamp] }; + vars.interval_start_to_entered_timestamps.insert(event.interval_start, entered_timestamp); + } + } else { + for entered_timestamp in vars.interval_start_to_entered_timestamps.values_mut() { + let in_match_window = (event.timestamp - entered_timestamp[step - 1].timestamp) <= args.conversion_window_limit as f64; + let already_reached_this_step = entered_timestamp[step].timestamp == entered_timestamp[step - 1].timestamp; + if in_match_window && !already_reached_this_step { + if exclusion { + return false; + } + let is_unmatched_step_attribution = self.breakdown_step.map(|breakdown_step| step == breakdown_step - 1).unwrap_or(false) && *prop_val != event.breakdown; + if !is_unmatched_step_attribution { + entered_timestamp[step] = EnteredTimestamp { + timestamp: entered_timestamp[step - 1].timestamp, + timings: { + let mut timings = entered_timestamp[step - 1].timings.clone(); + timings.push(event.timestamp); + timings + }, + }; + // check if we have hit the goal. if we have, remove it from the list and add it to the successful_timestamps + if entered_timestamp[args.num_steps].timestamp != 0.0 { + self.results.insert( + entered_timestamp[0].timestamp as u64, + ResultStruct(entered_timestamp[0].timestamp as u64, 1, prop_val.clone()) + ); + } else if step == args.from_step + 1 { + entered_timestamp[0].timings.push(1.0) + } + } + } + } + } + } + // If a strict funnel, clear all of the steps that we didn't match to + // If we are processing multiple events, skip this step, because ordering makes it complicated + if args.funnel_order_type == "strict" { + for entered_timestamp in vars.interval_start_to_entered_timestamps.values_mut() { + for i in 1..entered_timestamp.len() { + if !event.steps.contains(&(i as i8)) { + entered_timestamp[i] = DEFAULT_ENTERED_TIMESTAMP; + } + } + } + } + true + } +} \ No newline at end of file diff --git a/posthog/hogql/functions/mapping.py b/posthog/hogql/functions/mapping.py index 08bee305b933e..0b1830e21a264 100644 --- a/posthog/hogql/functions/mapping.py +++ b/posthog/hogql/functions/mapping.py @@ -388,7 +388,7 @@ def compare_types(arg_types: list[ConstantType], sig_arg_types: tuple[ConstantTy "reinterpretAsUUID": HogQLFunctionMeta("reinterpretAsUUID", 1, 1), "toInt": HogQLFunctionMeta("accurateCastOrNull", 1, 1, suffix_args=[ast.Constant(value="Int64")]), "_toInt64": HogQLFunctionMeta("toInt64", 1, 1), - "_toUInt64": HogQLFunctionMeta("toUInt64", 1, 1), + "_toUInt64": HogQLFunctionMeta("toUInt64", 1, 1, signatures=[((UnknownType(),), IntegerType())]), "_toUInt128": HogQLFunctionMeta("toUInt128", 1, 1), "toFloat": HogQLFunctionMeta("accurateCastOrNull", 1, 1, suffix_args=[ast.Constant(value="Float64")]), "toDecimal": HogQLFunctionMeta("accurateCastOrNull", 1, 1, suffix_args=[ast.Constant(value="Decimal64")]), diff --git a/posthog/hogql_queries/insights/funnels/funnel_trends_udf.py b/posthog/hogql_queries/insights/funnels/funnel_trends_udf.py index 2f928e014daf4..d171249520031 100644 --- a/posthog/hogql_queries/insights/funnels/funnel_trends_udf.py +++ b/posthog/hogql_queries/insights/funnels/funnel_trends_udf.py @@ -4,6 +4,7 @@ from posthog.hogql.constants import HogQLQuerySettings from posthog.hogql.parser import parse_select from posthog.hogql_queries.insights.funnels import FunnelTrends +from posthog.hogql_queries.insights.funnels.funnel_udf import udf_event_array_filter from posthog.hogql_queries.insights.utils.utils import get_start_of_interval_hogql_str from posthog.schema import BreakdownType, BreakdownAttributionType from posthog.utils import DATERANGE_MAP @@ -78,6 +79,7 @@ def get_query(self) -> ast.SelectQuery: parse_select( f""" SELECT + arraySort(t -> t.1, groupArray(tuple(toFloat(timestamp), _toUInt64(toDateTime({get_start_of_interval_hogql_str(self.context.interval.value, team=self.context.team, source='timestamp')})), {prop_selector}, arrayFilter((x) -> x != 0, [{steps}{exclusions}])))) as events_array, arrayJoin({fn}( {from_step}, {max_steps}, @@ -85,9 +87,9 @@ def get_query(self) -> ast.SelectQuery: '{breakdown_attribution_string}', '{self.context.funnelsFilter.funnelOrderType}', {prop_vals}, - arraySort(t -> t.1, groupArray(tuple(toFloat(timestamp), {get_start_of_interval_hogql_str(self.context.interval.value, team=self.context.team, source='timestamp')}, {prop_selector}, arrayFilter((x) -> x != 0, [{steps}{exclusions}])))) + {udf_event_array_filter(self.context.funnelsFilter.funnelOrderType)} )) as af_tuple, - toTimeZone(af_tuple.1, '{self.context.team.timezone}') as entrance_period_start, + toTimeZone(toDateTime(_toUInt64(af_tuple.1)), '{self.context.team.timezone}') as entrance_period_start, af_tuple.2 as success_bool, af_tuple.3 as breakdown FROM {{inner_event_query}} diff --git a/posthog/hogql_queries/insights/funnels/funnel_udf.py b/posthog/hogql_queries/insights/funnels/funnel_udf.py index e867975d04f45..a9a3ef9e3f5c4 100644 --- a/posthog/hogql_queries/insights/funnels/funnel_udf.py +++ b/posthog/hogql_queries/insights/funnels/funnel_udf.py @@ -3,13 +3,28 @@ from posthog.hogql import ast from posthog.hogql.parser import parse_select, parse_expr from posthog.hogql_queries.insights.funnels.base import FunnelBase -from posthog.schema import BreakdownType, BreakdownAttributionType +from posthog.schema import BreakdownType, BreakdownAttributionType, StepOrderValue from posthog.utils import DATERANGE_MAP TIMESTAMP_FORMAT = "%Y-%m-%d %H:%M:%S" HUMAN_READABLE_TIMESTAMP_FORMAT = "%-d-%b-%Y" +# This is used to reduce the number of events we look at in strict funnels +# We remove a non-matching event if there was already one before it (that don't have the same timestamp) +# arrayRotateRight turns [1,2,3] into [3,1,2] +# For some reason, this uses much less memory than using indexing in clickhouse to check the previous element +def udf_event_array_filter(funnelOrderType: StepOrderValue | None): + if funnelOrderType == "strict": + return f""" + arrayFilter( + (x, x2) -> not (empty(x.4) and empty(x2.4) and x.3 == x2.3 and x.1 > x2.1), + events_array, + arrayRotateRight(events_array, 1)) + """ + return "events_array" + + class FunnelUDF(FunnelBase): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) @@ -37,20 +52,6 @@ def conversion_window_limit(self) -> int: self.context.funnelWindowInterval * DATERANGE_MAP[self.context.funnelWindowIntervalUnit].total_seconds() ) - # This is used to reduce the number of events we look at in strict funnels - # We remove a non-matching event if there was already one before it (that don't have the same timestamp) - # arrayRotateRight turns [1,2,3] into [3,1,2] - # For some reason, this uses much less memory than using indexing in clickhouse to check the previous element - def _array_filter(self): - if self.context.funnelsFilter.funnelOrderType == "strict": - return f""" - arrayFilter( - (x, x2) -> not (empty(x.4) and empty(x2.4) and x.1 > x2.1), - events_array, - arrayRotateRight(events_array, 1)) - """ - return "events_array" - # This is the function that calls the UDF # This is used by both the query itself and the actors query def _inner_aggregation_query(self): @@ -114,7 +115,7 @@ def matched_event_arrays_selects(): '{breakdown_attribution_string}', '{self.context.funnelsFilter.funnelOrderType}', {prop_vals}, - {self._array_filter()} + {udf_event_array_filter(self.context.funnelsFilter.funnelOrderType)} )) as af_tuple, af_tuple.1 as step_reached, af_tuple.1 + 1 as steps, -- Backward compatibility diff --git a/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_correlation_actors_udf.ambr b/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_correlation_actors_udf.ambr index 7432cde6693bb..2490d1b6aa554 100644 --- a/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_correlation_actors_udf.ambr +++ b/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_correlation_actors_udf.ambr @@ -389,7 +389,8 @@ breakdown AS final_prop FROM (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1)])))) AS events_array, - arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, + arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(equals(x.3, x2.3), isNull(x.3) + and isNull(x2.3)), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, @@ -446,7 +447,8 @@ first_timestamp FROM (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1)])))) AS events_array, - arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, + arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(equals(x.3, x2.3), isNull(x.3) + and isNull(x2.3)), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, @@ -500,7 +502,8 @@ FROM (SELECT aggregation_target AS actor_id, matched_events_array[plus(step_reached, 1)] AS matching_events, (matched_events_array[1][1]).1 AS timestamp, nullIf((matched_events_array[2][1]).1, 0) AS final_timestamp, (matched_events_array[1][1]).1 AS first_timestamp, steps AS steps, final_timestamp, first_timestamp FROM - (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1)])))) AS events_array, arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, af_tuple.3 AS timings, af_tuple.4 AS matched_event_uuids_array_array, groupArray(tuple(timestamp, uuid, `$session_id`, `$window_id`)) AS user_events, mapFromArrays(arrayMap(x -> x.2, user_events), user_events) AS user_events_map, arrayMap(matched_event_uuids_array -> arrayMap(event_uuid -> user_events_map[event_uuid], arrayDistinct(matched_event_uuids_array)), matched_event_uuids_array_array) AS matched_events_array, aggregation_target AS aggregation_target + (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1)])))) AS events_array, arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(equals(x.3, x2.3), isNull(x.3) + and isNull(x2.3)), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, af_tuple.3 AS timings, af_tuple.4 AS matched_event_uuids_array_array, groupArray(tuple(timestamp, uuid, `$session_id`, `$window_id`)) AS user_events, mapFromArrays(arrayMap(x -> x.2, user_events), user_events) AS user_events_map, arrayMap(matched_event_uuids_array -> arrayMap(event_uuid -> user_events_map[event_uuid], arrayDistinct(matched_event_uuids_array)), matched_event_uuids_array_array) AS matched_events_array, aggregation_target AS aggregation_target FROM (SELECT toTimeZone(e.timestamp, 'UTC') AS timestamp, if(not(empty(e__override.distinct_id)), e__override.person_id, e.person_id) AS aggregation_target, e.uuid AS uuid, e.`$session_id` AS `$session_id`, e.`$window_id` AS `$window_id`, if(equals(e.event, '$pageview'), 1, 0) AS step_0, if(equals(e.event, 'insight analyzed'), 1, 0) AS step_1 FROM events AS e @@ -573,7 +576,8 @@ first_timestamp FROM (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1)])))) AS events_array, - arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, + arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(equals(x.3, x2.3), isNull(x.3) + and isNull(x2.3)), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, @@ -627,7 +631,8 @@ FROM (SELECT aggregation_target AS actor_id, matched_events_array[plus(step_reached, 1)] AS matching_events, (matched_events_array[1][1]).1 AS timestamp, nullIf((matched_events_array[2][1]).1, 0) AS final_timestamp, (matched_events_array[1][1]).1 AS first_timestamp, steps AS steps, final_timestamp, first_timestamp FROM - (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1)])))) AS events_array, arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, af_tuple.3 AS timings, af_tuple.4 AS matched_event_uuids_array_array, groupArray(tuple(timestamp, uuid, `$session_id`, `$window_id`)) AS user_events, mapFromArrays(arrayMap(x -> x.2, user_events), user_events) AS user_events_map, arrayMap(matched_event_uuids_array -> arrayMap(event_uuid -> user_events_map[event_uuid], arrayDistinct(matched_event_uuids_array)), matched_event_uuids_array_array) AS matched_events_array, aggregation_target AS aggregation_target + (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1)])))) AS events_array, arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(equals(x.3, x2.3), isNull(x.3) + and isNull(x2.3)), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, af_tuple.3 AS timings, af_tuple.4 AS matched_event_uuids_array_array, groupArray(tuple(timestamp, uuid, `$session_id`, `$window_id`)) AS user_events, mapFromArrays(arrayMap(x -> x.2, user_events), user_events) AS user_events_map, arrayMap(matched_event_uuids_array -> arrayMap(event_uuid -> user_events_map[event_uuid], arrayDistinct(matched_event_uuids_array)), matched_event_uuids_array_array) AS matched_events_array, aggregation_target AS aggregation_target FROM (SELECT toTimeZone(e.timestamp, 'UTC') AS timestamp, if(not(empty(e__override.distinct_id)), e__override.person_id, e.person_id) AS aggregation_target, e.uuid AS uuid, e.`$session_id` AS `$session_id`, e.`$window_id` AS `$window_id`, if(equals(e.event, '$pageview'), 1, 0) AS step_0, if(equals(e.event, 'insight analyzed'), 1, 0) AS step_1 FROM events AS e diff --git a/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_strict_persons_udf.ambr b/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_strict_persons_udf.ambr index 031aa7363bed0..118e756719797 100644 --- a/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_strict_persons_udf.ambr +++ b/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_strict_persons_udf.ambr @@ -9,7 +9,8 @@ matched_events_array[1] AS matching_events FROM (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1), multiply(3, step_2)])))) AS events_array, - arrayJoin(aggregate_funnel_array_v0(3, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, + arrayJoin(aggregate_funnel_array_v0(3, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(equals(x.3, x2.3), isNull(x.3) + and isNull(x2.3)), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, @@ -83,7 +84,8 @@ matched_events_array[2] AS matching_events FROM (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1), multiply(3, step_2)])))) AS events_array, - arrayJoin(aggregate_funnel_array_v0(3, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, + arrayJoin(aggregate_funnel_array_v0(3, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(equals(x.3, x2.3), isNull(x.3) + and isNull(x2.3)), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, @@ -157,7 +159,8 @@ matched_events_array[2] AS matching_events FROM (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1), multiply(3, step_2)])))) AS events_array, - arrayJoin(aggregate_funnel_array_v0(3, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, + arrayJoin(aggregate_funnel_array_v0(3, 1209600, 'first_touch', 'strict', [[]], arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(equals(x.3, x2.3), isNull(x.3) + and isNull(x2.3)), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, diff --git a/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_strict_udf.ambr b/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_strict_udf.ambr index d7a6897355738..7f457cf2cb4c9 100644 --- a/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_strict_udf.ambr +++ b/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_strict_udf.ambr @@ -15,7 +15,8 @@ if(ifNull(less(row_number, 25), 0), breakdown, ['Other']) AS final_prop FROM (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, prop, arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1)])))) AS events_array, - arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'first_touch', 'strict', groupUniqArray(prop), arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, + arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'first_touch', 'strict', groupUniqArray(prop), arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(equals(x.3, x2.3), isNull(x.3) + and isNull(x2.3)), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, @@ -84,7 +85,8 @@ if(ifNull(less(row_number, 25), 0), breakdown, ['Other']) AS final_prop FROM (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, prop, arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1)])))) AS events_array, - arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'step_1', 'strict', groupUniqArray(prop), arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, + arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'step_1', 'strict', groupUniqArray(prop), arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(equals(x.3, x2.3), isNull(x.3) + and isNull(x2.3)), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, @@ -160,7 +162,8 @@ if(ifNull(less(row_number, 25), 0), breakdown, ['Other']) AS final_prop FROM (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, prop, arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1)])))) AS events_array, - arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'first_touch', 'strict', groupUniqArray(prop), arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, + arrayJoin(aggregate_funnel_array_v0(2, 1209600, 'first_touch', 'strict', groupUniqArray(prop), arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(equals(x.3, x2.3), isNull(x.3) + and isNull(x2.3)), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, @@ -234,7 +237,8 @@ if(ifNull(less(row_number, 25), 0), breakdown, 'Other') AS final_prop FROM (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, prop, arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1), multiply(3, step_2)])))) AS events_array, - arrayJoin(aggregate_funnel_v0(3, 1209600, 'first_touch', 'strict', groupUniqArray(prop), arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, + arrayJoin(aggregate_funnel_v0(3, 1209600, 'first_touch', 'strict', groupUniqArray(prop), arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(equals(x.3, x2.3), isNull(x.3) + and isNull(x2.3)), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, @@ -311,7 +315,8 @@ if(ifNull(less(row_number, 25), 0), breakdown, 'Other') AS final_prop FROM (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, prop, arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1), multiply(3, step_2)])))) AS events_array, - arrayJoin(aggregate_funnel_v0(3, 1209600, 'first_touch', 'strict', groupUniqArray(prop), arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, + arrayJoin(aggregate_funnel_v0(3, 1209600, 'first_touch', 'strict', groupUniqArray(prop), arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(equals(x.3, x2.3), isNull(x.3) + and isNull(x2.3)), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, @@ -388,7 +393,8 @@ if(ifNull(less(row_number, 25), 0), breakdown, 'Other') AS final_prop FROM (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), uuid, prop, arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1), multiply(3, step_2)])))) AS events_array, - arrayJoin(aggregate_funnel_v0(3, 1209600, 'first_touch', 'strict', groupUniqArray(prop), arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, + arrayJoin(aggregate_funnel_v0(3, 1209600, 'first_touch', 'strict', groupUniqArray(prop), arrayFilter((x, x2) -> not(and(empty(x.4), empty(x2.4), ifNull(equals(x.3, x2.3), isNull(x.3) + and isNull(x2.3)), ifNull(greater(x.1, x2.1), 0))), events_array, arrayRotateRight(events_array, 1)))) AS af_tuple, af_tuple.1 AS step_reached, plus(af_tuple.1, 1) AS steps, af_tuple.2 AS breakdown, diff --git a/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_trends_udf.ambr b/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_trends_udf.ambr index bded4b095c3f5..043f02570c02f 100644 --- a/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_trends_udf.ambr +++ b/posthog/hogql_queries/insights/funnels/test/__snapshots__/test_funnel_trends_udf.ambr @@ -7,8 +7,9 @@ if(ifNull(greater(reached_from_step_count, 0), 0), round(multiply(divide(reached_to_step_count, reached_from_step_count), 100), 2), 0) AS conversion_rate, data.breakdown AS prop FROM - (SELECT arrayJoin(aggregate_funnel_array_trends_v0(0, 3, 1209600, 'first_touch', 'ordered', [[]], arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), toStartOfDay(timestamp), [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1), multiply(3, step_2)])))))) AS af_tuple, - toTimeZone(af_tuple.1, 'UTC') AS entrance_period_start, + (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), toUInt64(toDateTime(toStartOfDay(timestamp), 'UTC')), [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1), multiply(3, step_2)])))) AS events_array, + arrayJoin(aggregate_funnel_array_trends_v0(0, 3, 1209600, 'first_touch', 'ordered', [[]], events_array)) AS af_tuple, + toTimeZone(toDateTime(toUInt64(af_tuple.1), 'UTC'), 'UTC') AS entrance_period_start, af_tuple.2 AS success_bool, af_tuple.3 AS breakdown FROM @@ -52,8 +53,9 @@ if(ifNull(greater(reached_from_step_count, 0), 0), round(multiply(divide(reached_to_step_count, reached_from_step_count), 100), 2), 0) AS conversion_rate, data.breakdown AS prop FROM - (SELECT arrayJoin(aggregate_funnel_array_trends_v0(0, 3, 1209600, 'first_touch', 'ordered', [[]], arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), toStartOfDay(timestamp), [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1), multiply(3, step_2)])))))) AS af_tuple, - toTimeZone(af_tuple.1, 'US/Pacific') AS entrance_period_start, + (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), toUInt64(toDateTime(toStartOfDay(timestamp), 'US/Pacific')), [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1), multiply(3, step_2)])))) AS events_array, + arrayJoin(aggregate_funnel_array_trends_v0(0, 3, 1209600, 'first_touch', 'ordered', [[]], events_array)) AS af_tuple, + toTimeZone(toDateTime(toUInt64(af_tuple.1), 'US/Pacific'), 'US/Pacific') AS entrance_period_start, af_tuple.2 AS success_bool, af_tuple.3 AS breakdown FROM @@ -97,8 +99,9 @@ if(ifNull(greater(reached_from_step_count, 0), 0), round(multiply(divide(reached_to_step_count, reached_from_step_count), 100), 2), 0) AS conversion_rate, data.breakdown AS prop FROM - (SELECT arrayJoin(aggregate_funnel_array_trends_v0(0, 3, 1209600, 'first_touch', 'ordered', [[]], arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), toStartOfWeek(timestamp, 0), [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1), multiply(3, step_2)])))))) AS af_tuple, - toTimeZone(af_tuple.1, 'UTC') AS entrance_period_start, + (SELECT arraySort(t -> t.1, groupArray(tuple(accurateCastOrNull(timestamp, 'Float64'), toUInt64(toDateTime(toStartOfWeek(timestamp, 0), 'UTC')), [], arrayFilter(x -> ifNull(notEquals(x, 0), 1), [multiply(1, step_0), multiply(2, step_1), multiply(3, step_2)])))) AS events_array, + arrayJoin(aggregate_funnel_array_trends_v0(0, 3, 1209600, 'first_touch', 'ordered', [[]], events_array)) AS af_tuple, + toTimeZone(toDateTime(toUInt64(af_tuple.1), 'UTC'), 'UTC') AS entrance_period_start, af_tuple.2 AS success_bool, af_tuple.3 AS breakdown FROM diff --git a/posthog/hogql_queries/insights/funnels/test/test_funnel_strict_udf.py b/posthog/hogql_queries/insights/funnels/test/test_funnel_strict_udf.py index 934f55babcc0b..6b6eb7d0f06db 100644 --- a/posthog/hogql_queries/insights/funnels/test/test_funnel_strict_udf.py +++ b/posthog/hogql_queries/insights/funnels/test/test_funnel_strict_udf.py @@ -4,9 +4,10 @@ from freezegun import freeze_time from hogql_parser import parse_expr -from posthog.constants import INSIGHT_FUNNELS +from posthog.constants import INSIGHT_FUNNELS, FunnelOrderType from posthog.hogql.constants import HogQLGlobalSettings, MAX_BYTES_BEFORE_EXTERNAL_GROUP_BY from posthog.hogql.query import execute_hogql_query +from posthog.hogql_queries.insights.funnels.funnel_udf import udf_event_array_filter from posthog.hogql_queries.insights.funnels.funnels_query_runner import FunnelsQueryRunner from posthog.hogql_queries.insights.funnels.test.test_funnel_strict import ( BaseTestFunnelStrictStepsBreakdown, @@ -15,7 +16,14 @@ BaseTestFunnelStrictStepsConversionTime, ) from posthog.hogql_queries.legacy_compatibility.filter_to_query import filter_to_query -from posthog.schema import FunnelsQuery +from posthog.schema import ( + FunnelsQuery, + EventsNode, + BreakdownFilter, + FunnelsFilter, + BreakdownAttributionType, + StepOrderValue, +) from posthog.test.base import _create_person, _create_event @@ -49,7 +57,9 @@ def test_redundant_event_filtering_strict_funnel(self): query = cast(FunnelsQuery, filter_to_query(filters)) runner = FunnelsQueryRunner(query=query, team=self.team) inner_aggregation_query = runner.funnel_class._inner_aggregation_query() - inner_aggregation_query.select.append(parse_expr(f"{runner.funnel_class._array_filter()} AS filtered_array")) + inner_aggregation_query.select.append( + parse_expr(f"{udf_event_array_filter(StepOrderValue.STRICT)} AS filtered_array") + ) inner_aggregation_query.having = None response = execute_hogql_query( query_type="FunnelsQuery", @@ -64,6 +74,43 @@ def test_redundant_event_filtering_strict_funnel(self): # Make sure the events have been condensed down to one self.assertEqual(1, len(response.results[0][-1])) + def test_different_prop_val_in_strict_filter(self): + funnels_query = FunnelsQuery( + series=[EventsNode(event="first"), EventsNode(event="second")], + breakdownFilter=BreakdownFilter(breakdown="bd"), + funnelsFilter=FunnelsFilter(funnelOrderType=FunnelOrderType.STRICT), + ) + + _create_person( + distinct_ids=["many_other_events"], + team_id=self.team.pk, + properties={"test": "okay"}, + ) + _create_event(team=self.team, event="first", distinct_id="many_other_events", properties={"bd": "one"}) + _create_event(team=self.team, event="first", distinct_id="many_other_events", properties={"bd": "two"}) + _create_event(team=self.team, event="unmatched", distinct_id="many_other_events", properties={"bd": "one"}) + _create_event(team=self.team, event="unmatched", distinct_id="many_other_events", properties={"bd": "two"}) + _create_event(team=self.team, event="second", distinct_id="many_other_events", properties={"bd": "one"}) + _create_event(team=self.team, event="second", distinct_id="many_other_events", properties={"bd": "two"}) + + # First Touchpoint (just "one") + results = FunnelsQueryRunner(query=funnels_query, team=self.team).calculate().results + + assert 2 == len(results[0]) + assert results[0][-1]["count"] == 0 + assert all(result["breakdown"] == ["one"] for result in results[0]) + + # All events attribution + assert funnels_query.funnelsFilter is not None + funnels_query.funnelsFilter.breakdownAttributionType = BreakdownAttributionType.ALL_EVENTS + results = FunnelsQueryRunner(query=funnels_query, team=self.team).calculate().results + + assert 2 == len(results) + one = next(x for x in results if x[0]["breakdown"] == ["one"]) + assert one[-1]["count"] == 0 + two = next(x for x in results if x[0]["breakdown"] == ["two"]) + assert two[-1]["count"] == 0 + def test_multiple_events_same_timestamp_doesnt_blow_up(self): _create_person(distinct_ids=["test"], team_id=self.team.pk) with freeze_time("2024-01-10T12:01:00"): diff --git a/posthog/hogql_queries/insights/funnels/test/test_funnel_trends.py b/posthog/hogql_queries/insights/funnels/test/test_funnel_trends.py index d7f8d326e2a7d..cb1ab3e0653fd 100644 --- a/posthog/hogql_queries/insights/funnels/test/test_funnel_trends.py +++ b/posthog/hogql_queries/insights/funnels/test/test_funnel_trends.py @@ -2,7 +2,9 @@ from typing import cast from zoneinfo import ZoneInfo + from freezegun.api import freeze_time +from parameterized import parameterized from posthog.constants import INSIGHT_FUNNELS, TRENDS_LINEAR, FunnelOrderType from posthog.hogql_queries.insights.funnels.funnels_query_runner import FunnelsQueryRunner @@ -101,7 +103,11 @@ def test_no_event_in_period(self): self.assertEqual(len(results), 7) self.assertEqual(formatted_results[0]["days"][0], "2021-06-07") - def test_only_one_user_reached_one_step(self): + @parameterized.expand(["US/Pacific", "UTC"]) + def test_only_one_user_reached_one_step(self, timezone): + self.team.timezone = timezone + self.team.save() + journeys_for( {"user a": [{"event": "step one", "timestamp": datetime(2021, 6, 7, 19)}]}, self.team, @@ -133,43 +139,43 @@ def test_only_one_user_reached_one_step(self): "reached_to_step_count": 0, "conversion_rate": 0.0, "reached_from_step_count": 1, - "timestamp": datetime(2021, 6, 7, 0, 0).replace(tzinfo=ZoneInfo("UTC")), + "timestamp": datetime(2021, 6, 7, 0, 0).replace(tzinfo=ZoneInfo(timezone)), }, { "reached_to_step_count": 0, "conversion_rate": 0.0, "reached_from_step_count": 0, - "timestamp": datetime(2021, 6, 8, 0, 0).replace(tzinfo=ZoneInfo("UTC")), + "timestamp": datetime(2021, 6, 8, 0, 0).replace(tzinfo=ZoneInfo(timezone)), }, { "reached_to_step_count": 0, "conversion_rate": 0.0, "reached_from_step_count": 0, - "timestamp": datetime(2021, 6, 9, 0, 0).replace(tzinfo=ZoneInfo("UTC")), + "timestamp": datetime(2021, 6, 9, 0, 0).replace(tzinfo=ZoneInfo(timezone)), }, { "reached_to_step_count": 0, "conversion_rate": 0.0, "reached_from_step_count": 0, - "timestamp": datetime(2021, 6, 10, 0, 0).replace(tzinfo=ZoneInfo("UTC")), + "timestamp": datetime(2021, 6, 10, 0, 0).replace(tzinfo=ZoneInfo(timezone)), }, { "reached_to_step_count": 0, "conversion_rate": 0.0, "reached_from_step_count": 0, - "timestamp": datetime(2021, 6, 11, 0, 0).replace(tzinfo=ZoneInfo("UTC")), + "timestamp": datetime(2021, 6, 11, 0, 0).replace(tzinfo=ZoneInfo(timezone)), }, { "reached_to_step_count": 0, "conversion_rate": 0.0, "reached_from_step_count": 0, - "timestamp": datetime(2021, 6, 12, 0, 0).replace(tzinfo=ZoneInfo("UTC")), + "timestamp": datetime(2021, 6, 12, 0, 0).replace(tzinfo=ZoneInfo(timezone)), }, { "reached_to_step_count": 0, "conversion_rate": 0.0, "reached_from_step_count": 0, - "timestamp": datetime(2021, 6, 13, 0, 0).replace(tzinfo=ZoneInfo("UTC")), + "timestamp": datetime(2021, 6, 13, 0, 0).replace(tzinfo=ZoneInfo(timezone)), }, ], ) @@ -292,7 +298,11 @@ def test_week_interval(self): self.assertEqual(2, len(results)) self.assertEqual([person["distinct_ids"] for person in persons], [["user_one"]]) - def test_month_interval(self): + @parameterized.expand(["US/Pacific", "UTC"]) + def test_month_interval(self, timezone): + self.team.timezone = timezone + self.team.save() + filters = { "insight": INSIGHT_FUNNELS, "funnel_viz_type": "trends", @@ -344,15 +354,15 @@ def test_month_interval(self): "timestamp": date(2020, 3, 1), }, { - "conversion_rate": 0.0, - "reached_from_step_count": 0, - "reached_to_step_count": 0, + "conversion_rate": 100.0 if timezone == "US/Pacific" else 0.0, + "reached_from_step_count": 1 if timezone == "US/Pacific" else 0, + "reached_to_step_count": 1 if timezone == "US/Pacific" else 0, "timestamp": date(2020, 4, 1), }, { - "conversion_rate": 100.0, - "reached_from_step_count": 1, - "reached_to_step_count": 1, + "conversion_rate": 100.0 if timezone == "UTC" else 0.0, + "reached_from_step_count": 1 if timezone == "UTC" else 0, + "reached_to_step_count": 1 if timezone == "UTC" else 0, "timestamp": date(2020, 5, 1), }, { @@ -369,8 +379,8 @@ def test_month_interval(self): }, ], ) - - persons = self._get_actors_at_step(filters, "2020-05-01 00:00:00", False) + entrance_period_start = "2020-05-01 00:00:00" if timezone == "UTC" else "2020-04-01 00:00:00" + persons = self._get_actors_at_step(filters, entrance_period_start, False) self.assertEqual([person["distinct_ids"] for person in persons], [["user_one"]]) diff --git a/posthog/hogql_queries/insights/funnels/test/test_funnel_trends_udf.py b/posthog/hogql_queries/insights/funnels/test/test_funnel_trends_udf.py index 2829bb93ce7dc..d341f7c272be3 100644 --- a/posthog/hogql_queries/insights/funnels/test/test_funnel_trends_udf.py +++ b/posthog/hogql_queries/insights/funnels/test/test_funnel_trends_udf.py @@ -1,11 +1,23 @@ +import datetime from typing import cast from unittest.mock import patch, Mock -from posthog.constants import INSIGHT_FUNNELS, TRENDS_LINEAR +from posthog.constants import INSIGHT_FUNNELS, TRENDS_LINEAR, FunnelOrderType from posthog.hogql_queries.insights.funnels.funnels_query_runner import FunnelsQueryRunner from posthog.hogql_queries.insights.funnels.test.test_funnel_trends import BaseTestFunnelTrends from posthog.hogql_queries.legacy_compatibility.filter_to_query import filter_to_query -from posthog.schema import FunnelsQuery, FunnelsQueryResponse +from posthog.schema import ( + FunnelsQuery, + FunnelsQueryResponse, + EventsNode, + BreakdownFilter, + FunnelsFilter, + FunnelVizType, + BreakdownAttributionType, + InsightDateRange, + IntervalType, +) +from posthog.test.base import _create_person, _create_event @patch( @@ -53,3 +65,111 @@ def test_assert_steps_flag_is_off(self): results = cast(FunnelsQueryResponse, FunnelsQueryRunner(query=query, team=self.team).calculate()) self.assertFalse(results.isUdf) + + def test_different_prop_val_in_strict_filter(self): + funnels_query = FunnelsQuery( + series=[EventsNode(event="first"), EventsNode(event="second")], + breakdownFilter=BreakdownFilter(breakdown="bd"), + dateRange=InsightDateRange(date_from="2024-01-01", date_to="2024-01-08"), + interval=IntervalType.DAY, + funnelsFilter=FunnelsFilter(funnelOrderType=FunnelOrderType.STRICT, funnelVizType=FunnelVizType.TRENDS), + ) + + _create_person( + distinct_ids=["many_other_events"], + team_id=self.team.pk, + properties={"test": "okay"}, + ) + _create_event( + team=self.team, + event="first", + distinct_id="many_other_events", + properties={"bd": "one"}, + timestamp=datetime.datetime(2024, 1, 2), + ) + _create_event( + team=self.team, + event="first", + distinct_id="many_other_events", + properties={"bd": "two"}, + timestamp=datetime.datetime(2024, 1, 3), + ) + _create_event( + team=self.team, + event="unmatched", + distinct_id="many_other_events", + properties={"bd": "one"}, + timestamp=datetime.datetime(2024, 1, 4), + ) + _create_event( + team=self.team, + event="unmatched", + distinct_id="many_other_events", + properties={"bd": "two"}, + timestamp=datetime.datetime(2024, 1, 5), + ) + _create_event( + team=self.team, + event="second", + distinct_id="many_other_events", + properties={"bd": "one"}, + timestamp=datetime.datetime(2024, 1, 6), + ) + _create_event( + team=self.team, + event="second", + distinct_id="many_other_events", + properties={"bd": "two"}, + timestamp=datetime.datetime(2024, 1, 7), + ) + + # First Touchpoint (just "one") + results = FunnelsQueryRunner(query=funnels_query, team=self.team).calculate().results + + self.assertEqual( + [ + { + "breakdown_value": ["one"], + "count": 8, + "data": [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + ], + "days": [ + "2024-01-01", + "2024-01-02", + "2024-01-03", + "2024-01-04", + "2024-01-05", + "2024-01-06", + "2024-01-07", + "2024-01-08", + ], + "labels": [ + "1-Jan-2024", + "2-Jan-2024", + "3-Jan-2024", + "4-Jan-2024", + "5-Jan-2024", + "6-Jan-2024", + "7-Jan-2024", + "8-Jan-2024", + ], + } + ], + results, + ) + + # All events attribution + assert funnels_query.funnelsFilter is not None + funnels_query.funnelsFilter.breakdownAttributionType = BreakdownAttributionType.ALL_EVENTS + results = FunnelsQueryRunner(query=funnels_query, team=self.team).calculate().results + + assert len(results) == 2 + assert all(data == 0 for result in results for data in result["data"]) diff --git a/posthog/user_scripts/aggregate_funnel b/posthog/user_scripts/aggregate_funnel index c85d180971e38..e62dd751484cb 100755 --- a/posthog/user_scripts/aggregate_funnel +++ b/posthog/user_scripts/aggregate_funnel @@ -3,7 +3,7 @@ DIR_NAME=$(dirname "$0") case $( uname -m ) in -aarch64) $DIR_NAME/aggregate_funnel_aarch64;; -*) $DIR_NAME/aggregate_funnel_x86_64;; +aarch64) $DIR_NAME/aggregate_funnel_aarch64 "$@";; +*) $DIR_NAME/aggregate_funnel_x86_64 "$@";; esac diff --git a/posthog/user_scripts/aggregate_funnel_aarch64 b/posthog/user_scripts/aggregate_funnel_aarch64 index c6169148db0b6d1e25a98baba5934b638d7765f8..aabb3ff28f7cd0ad70497820998d00c35237ac81 100755 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calculate_funnel_trends_from_user_events, parse_args import sys import json if __name__ == "__main__": for line in sys.stdin: try: - calculate_funnel_trends_from_user_events(*parse_args(line)) + print(json.dumps({"result": line})) # noqa: T201 + # calculate_funnel_trends_from_user_events(*parse_args(line)) except Exception as e: print(json.dumps({"result": json.dumps(str(e))}), end="\n") # noqa: T201 sys.stdout.flush() diff --git a/posthog/user_scripts/aggregate_funnel_trends.py b/posthog/user_scripts/aggregate_funnel_trends.py index cde3a30928584..3b7d8a5816b3a 100755 --- a/posthog/user_scripts/aggregate_funnel_trends.py +++ b/posthog/user_scripts/aggregate_funnel_trends.py @@ -62,7 +62,7 @@ def loop_prop_val(prop_val): if breakdown_attribution_type == "all_events" else events ) - list_of_entered_timestamps = [] + interval_start_to_entered_timestamps = {} for timestamp, interval_start, breakdown, steps in filtered_events: for step in reversed(steps): @@ -73,15 +73,17 @@ def loop_prop_val(prop_val): # Special code to handle the first step # Potential Optimization: we could skip tracking here if the user has already completed the funnel for this interval if step == 1: - entered_timestamp = [default_entered_timestamp] * (num_steps + 1) - # Set the interval start at 0, which is what we want to return if this works. - # For strict funnels, we need to track if the "from_step" has been hit - # Abuse the timings field on the 0th index entered_timestamp to have the elt True if we have - entered_timestamp[0] = EnteredTimestamp(interval_start, [True] if from_step == 0 else []) - entered_timestamp[1] = EnteredTimestamp(timestamp, [timestamp]) - list_of_entered_timestamps.append(entered_timestamp) + if interval_start not in interval_start_to_entered_timestamps and interval_start not in results: + entered_timestamp = [default_entered_timestamp] * (num_steps + 1) + # Set the interval start at 0, which is what we want to return if this works. + # For strict funnels, we need to track if the "from_step" has been hit + # Abuse the timings field on the 0th index entered_timestamp to have the elt True if we have + entered_timestamp[0] = EnteredTimestamp(interval_start, [True] if from_step == 0 else []) + entered_timestamp[1] = EnteredTimestamp(timestamp, [timestamp]) + interval_start_to_entered_timestamps[interval_start] = entered_timestamp + # list_of_entered_timestamps.append(entered_timestamp) else: - for entered_timestamp in list_of_entered_timestamps[:]: + for entered_timestamp in interval_start_to_entered_timestamps.values(): in_match_window = ( timestamp - entered_timestamp[step - 1].timestamp <= conversion_window_limit_seconds ) @@ -103,20 +105,19 @@ def loop_prop_val(prop_val): # check if we have hit the goal. if we have, remove it from the list and add it to the successful_timestamps if entered_timestamp[num_steps].timestamp > 0: results[entered_timestamp[0].timestamp] = (1, prop_val) - list_of_entered_timestamps.remove(entered_timestamp) # If we have hit the from_step threshold, record it (abuse the timings field) elif step == from_step + 1: entered_timestamp[0].timings.append(True) # At the end of the event, clear all steps that weren't done by that event if funnel_order_type == "strict": - for entered_timestamp in list_of_entered_timestamps[:]: + for entered_timestamp in interval_start_to_entered_timestamps.values(): for i in range(1, len(entered_timestamp)): if i not in steps: entered_timestamp[i] = default_entered_timestamp # At this point, everything left in entered_timestamps is a failure, if it has made it to from_step - for entered_timestamp in list_of_entered_timestamps: + for entered_timestamp in interval_start_to_entered_timestamps.values(): if entered_timestamp[0].timestamp not in results and len(entered_timestamp[0].timings) > 0: results[entered_timestamp[0].timestamp] = (-1, prop_val) diff --git a/posthog/user_scripts/aggregate_funnel_x86_64 b/posthog/user_scripts/aggregate_funnel_x86_64 index 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Do not edit this, only edit the value JSONEachRow - aggregate_funnel + aggregate_funnel steps 600 @@ -64,7 +64,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the value JSONEachRow - aggregate_funnel + aggregate_funnel steps 600 @@ -98,7 +98,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the value JSONEachRow - aggregate_funnel + aggregate_funnel steps 600 @@ -139,7 +139,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the executable_pool aggregate_funnel_trends - Array(Tuple(DateTime, Int8, Nullable(String))) + Array(Tuple(UInt64, Int8, Nullable(String))) result UInt8 @@ -170,11 +170,11 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), Nullable(String), Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, Nullable(String), Array(Int8))) value JSONEachRow - aggregate_funnel_trends.py + aggregate_funnel trends 600 @@ -182,7 +182,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the executable_pool aggregate_funnel_array_trends - Array(Tuple(DateTime, Int8, Array(String))) + Array(Tuple(UInt64, Int8, Array(String))) result UInt8 @@ -209,11 +209,11 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), Array(String), Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, Array(String), Array(Int8))) value JSONEachRow - aggregate_funnel_array_trends.py + aggregate_funnel trends 600 @@ -221,7 +221,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the executable_pool aggregate_funnel_cohort_trends - Array(Tuple(DateTime, Int8, UInt64)) + Array(Tuple(UInt64, Int8, UInt64)) result UInt8 @@ -248,11 +248,11 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), UInt64, Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, UInt64, Array(Int8))) value JSONEachRow - aggregate_funnel_cohort_trends.py + aggregate_funnel trends 600 @@ -286,7 +286,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), Array(String), Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, Array(String), Array(Int8))) value JSONEachRow @@ -323,7 +323,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the value JSONEachRow - v0/aggregate_funnel + v0/aggregate_funnel steps 600 @@ -357,7 +357,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the value JSONEachRow - v0/aggregate_funnel + v0/aggregate_funnel steps 600 @@ -391,7 +391,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the value JSONEachRow - v0/aggregate_funnel + v0/aggregate_funnel steps 600 @@ -432,7 +432,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the executable_pool aggregate_funnel_trends_v0 - Array(Tuple(DateTime, Int8, Nullable(String))) + Array(Tuple(UInt64, Int8, Nullable(String))) result UInt8 @@ -463,11 +463,11 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), Nullable(String), Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, Nullable(String), Array(Int8))) value JSONEachRow - v0/aggregate_funnel_trends.py + v0/aggregate_funnel trends 600 @@ -475,7 +475,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the executable_pool aggregate_funnel_array_trends_v0 - Array(Tuple(DateTime, Int8, Array(String))) + Array(Tuple(UInt64, Int8, Array(String))) result UInt8 @@ -502,11 +502,11 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), Array(String), Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, Array(String), Array(Int8))) value JSONEachRow - v0/aggregate_funnel_array_trends.py + v0/aggregate_funnel trends 600 @@ -514,7 +514,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the executable_pool aggregate_funnel_cohort_trends_v0 - Array(Tuple(DateTime, Int8, UInt64)) + Array(Tuple(UInt64, Int8, UInt64)) result UInt8 @@ -541,11 +541,11 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), UInt64, Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, UInt64, Array(Int8))) value JSONEachRow - v0/aggregate_funnel_cohort_trends.py + v0/aggregate_funnel trends 600 @@ -579,7 +579,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), Array(String), Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, Array(String), Array(Int8))) value JSONEachRow diff --git a/posthog/user_scripts/v0/aggregate_funnel b/posthog/user_scripts/v0/aggregate_funnel index c85d180971e38..e62dd751484cb 100755 --- a/posthog/user_scripts/v0/aggregate_funnel +++ b/posthog/user_scripts/v0/aggregate_funnel @@ -3,7 +3,7 @@ DIR_NAME=$(dirname "$0") case $( uname -m ) in -aarch64) $DIR_NAME/aggregate_funnel_aarch64;; -*) $DIR_NAME/aggregate_funnel_x86_64;; +aarch64) $DIR_NAME/aggregate_funnel_aarch64 "$@";; +*) $DIR_NAME/aggregate_funnel_x86_64 "$@";; esac diff --git a/posthog/user_scripts/v0/aggregate_funnel_aarch64 b/posthog/user_scripts/v0/aggregate_funnel_aarch64 index c6169148db0b6d1e25a98baba5934b638d7765f8..aabb3ff28f7cd0ad70497820998d00c35237ac81 100755 GIT binary patch delta 249668 zcmce<3s_Xu8b7?&9)tmJCKA(qX)^Dx# 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calculate_funnel_trends_from_user_events, parse_args import sys import json if __name__ == "__main__": for line in sys.stdin: try: - calculate_funnel_trends_from_user_events(*parse_args(line)) + print(json.dumps({"result": line})) # noqa: T201 + # calculate_funnel_trends_from_user_events(*parse_args(line)) except Exception as e: print(json.dumps({"result": json.dumps(str(e))}), end="\n") # noqa: T201 sys.stdout.flush() diff --git a/posthog/user_scripts/v0/aggregate_funnel_trends.py b/posthog/user_scripts/v0/aggregate_funnel_trends.py index cde3a30928584..3b7d8a5816b3a 100755 --- a/posthog/user_scripts/v0/aggregate_funnel_trends.py +++ b/posthog/user_scripts/v0/aggregate_funnel_trends.py @@ -62,7 +62,7 @@ def loop_prop_val(prop_val): if breakdown_attribution_type == "all_events" else events ) - list_of_entered_timestamps = [] + interval_start_to_entered_timestamps = {} for timestamp, interval_start, breakdown, steps in filtered_events: for step in reversed(steps): @@ -73,15 +73,17 @@ def loop_prop_val(prop_val): # Special code to handle the first step # Potential Optimization: we could skip tracking here if the user has already completed the funnel for this interval if step == 1: - entered_timestamp = [default_entered_timestamp] * (num_steps + 1) - # Set the interval start at 0, which is what we want to return if this works. - # For strict funnels, we need to track if the "from_step" has been hit - # Abuse the timings field on the 0th index entered_timestamp to have the elt True if we have - entered_timestamp[0] = EnteredTimestamp(interval_start, [True] if from_step == 0 else []) - entered_timestamp[1] = EnteredTimestamp(timestamp, [timestamp]) - list_of_entered_timestamps.append(entered_timestamp) + if interval_start not in interval_start_to_entered_timestamps and interval_start not in results: + entered_timestamp = [default_entered_timestamp] * (num_steps + 1) + # Set the interval start at 0, which is what we want to return if this works. + # For strict funnels, we need to track if the "from_step" has been hit + # Abuse the timings field on the 0th index entered_timestamp to have the elt True if we have + entered_timestamp[0] = EnteredTimestamp(interval_start, [True] if from_step == 0 else []) + entered_timestamp[1] = EnteredTimestamp(timestamp, [timestamp]) + interval_start_to_entered_timestamps[interval_start] = entered_timestamp + # list_of_entered_timestamps.append(entered_timestamp) else: - for entered_timestamp in list_of_entered_timestamps[:]: + for entered_timestamp in interval_start_to_entered_timestamps.values(): in_match_window = ( timestamp - entered_timestamp[step - 1].timestamp <= conversion_window_limit_seconds ) @@ -103,20 +105,19 @@ def loop_prop_val(prop_val): # check if we have hit the goal. if we have, remove it from the list and add it to the successful_timestamps if entered_timestamp[num_steps].timestamp > 0: results[entered_timestamp[0].timestamp] = (1, prop_val) - list_of_entered_timestamps.remove(entered_timestamp) # If we have hit the from_step threshold, record it (abuse the timings field) elif step == from_step + 1: entered_timestamp[0].timings.append(True) # At the end of the event, clear all steps that weren't done by that event if funnel_order_type == "strict": - for entered_timestamp in list_of_entered_timestamps[:]: + for entered_timestamp in interval_start_to_entered_timestamps.values(): for i in range(1, len(entered_timestamp)): if i not in steps: entered_timestamp[i] = default_entered_timestamp # At this point, everything left in entered_timestamps is a failure, if it has made it to from_step - for entered_timestamp in list_of_entered_timestamps: + for entered_timestamp in interval_start_to_entered_timestamps.values(): if entered_timestamp[0].timestamp not in results and len(entered_timestamp[0].timings) > 0: results[entered_timestamp[0].timestamp] = (-1, prop_val) diff --git a/posthog/user_scripts/v0/aggregate_funnel_x86_64 b/posthog/user_scripts/v0/aggregate_funnel_x86_64 index 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Do not edit this, only edit the value JSONEachRow - aggregate_funnel + aggregate_funnel steps 600 @@ -64,7 +64,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the value JSONEachRow - aggregate_funnel + aggregate_funnel steps 600 @@ -98,7 +98,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the value JSONEachRow - aggregate_funnel + aggregate_funnel steps 600 @@ -139,7 +139,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the executable_pool aggregate_funnel_trends - Array(Tuple(DateTime, Int8, Nullable(String))) + Array(Tuple(UInt64, Int8, Nullable(String))) result UInt8 @@ -170,11 +170,11 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), Nullable(String), Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, Nullable(String), Array(Int8))) value JSONEachRow - aggregate_funnel_trends.py + aggregate_funnel trends 600 @@ -182,7 +182,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the executable_pool aggregate_funnel_array_trends - Array(Tuple(DateTime, Int8, Array(String))) + Array(Tuple(UInt64, Int8, Array(String))) result UInt8 @@ -209,11 +209,11 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), Array(String), Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, Array(String), Array(Int8))) value JSONEachRow - aggregate_funnel_array_trends.py + aggregate_funnel trends 600 @@ -221,7 +221,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the executable_pool aggregate_funnel_cohort_trends - Array(Tuple(DateTime, Int8, UInt64)) + Array(Tuple(UInt64, Int8, UInt64)) result UInt8 @@ -248,11 +248,11 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), UInt64, Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, UInt64, Array(Int8))) value JSONEachRow - aggregate_funnel_cohort_trends.py + aggregate_funnel trends 600 @@ -286,7 +286,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), Array(String), Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, Array(String), Array(Int8))) value JSONEachRow @@ -323,7 +323,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the value JSONEachRow - v0/aggregate_funnel + v0/aggregate_funnel steps 600 @@ -357,7 +357,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the value JSONEachRow - v0/aggregate_funnel + v0/aggregate_funnel steps 600 @@ -391,7 +391,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the value JSONEachRow - v0/aggregate_funnel + v0/aggregate_funnel steps 600 @@ -432,7 +432,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the executable_pool aggregate_funnel_trends_v0 - Array(Tuple(DateTime, Int8, Nullable(String))) + Array(Tuple(UInt64, Int8, Nullable(String))) result UInt8 @@ -463,11 +463,11 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), Nullable(String), Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, Nullable(String), Array(Int8))) value JSONEachRow - v0/aggregate_funnel_trends.py + v0/aggregate_funnel trends 600 @@ -475,7 +475,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the executable_pool aggregate_funnel_array_trends_v0 - Array(Tuple(DateTime, Int8, Array(String))) + Array(Tuple(UInt64, Int8, Array(String))) result UInt8 @@ -502,11 +502,11 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), Array(String), Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, Array(String), Array(Int8))) value JSONEachRow - v0/aggregate_funnel_array_trends.py + v0/aggregate_funnel trends 600 @@ -514,7 +514,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the executable_pool aggregate_funnel_cohort_trends_v0 - Array(Tuple(DateTime, Int8, UInt64)) + Array(Tuple(UInt64, Int8, UInt64)) result UInt8 @@ -541,11 +541,11 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), UInt64, Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, UInt64, Array(Int8))) value JSONEachRow - v0/aggregate_funnel_cohort_trends.py + v0/aggregate_funnel trends 600 @@ -579,7 +579,7 @@ This file is autogenerated by udf_versioner.py. Do not edit this, only edit the prop_vals - Array(Tuple(Nullable(Float64), Nullable(DateTime), Array(String), Array(Int8))) + Array(Tuple(Nullable(Float64), UInt64, Array(String), Array(Int8))) value JSONEachRow