def __init__(
self,
dataset: Dataset,
params: ParamsType,
granularity: int,
query: Optional[str] = None,
selected_columns: Optional[List[str]] = None,
equations: Optional[List[str]] = None,
functions_acl: Optional[List[str]] = None,
limit: Optional[int] = 10000,
):
super().__init__(
dataset,
params,
auto_fields=False,
functions_acl=functions_acl,
equation_config={
"auto_add": True,
"aggregates_only": True
},
)
self.where, self.having = self.resolve_conditions(
query, use_aggregate_conditions=False)
self.limit = None if limit is None else Limit(limit)
# params depends on parse_query, and conditions being resolved first since there may be projects in conditions
self.where += self.resolve_params()
self.columns = self.resolve_select(selected_columns, equations)
self.granularity = Granularity(granularity)
# This is a timeseries, the groupby will always be time
self.groupby = [self.time_column]
def test_simple(self) -> None:
query = Query(
dataset="sessions",
match=Entity("org_sessions"),
select=[Column("org_id"), Column("project_id")],
groupby=[Column("org_id"), Column("project_id")],
where=[
Condition(Column("started"), Op.GTE,
datetime.utcnow() - timedelta(hours=6)),
Condition(Column("started"), Op.LT, datetime.utcnow()),
],
granularity=Granularity(3600),
)
response = self.app.post(
"/sessions/snql",
data=query.snuba(),
)
data = json.loads(response.data)
assert response.status_code == 200, response.data
assert len(data["data"]) == 2
assert data["data"][0]["org_id"] == self.org_id
assert data["data"][0]["project_id"] == self.project_id
assert data["data"][1]["org_id"] == self.org_id
assert data["data"][1]["project_id"] == self.project_id2
def build_project_usage_outcomes(start__stop, project):
start, stop = start__stop
# XXX(epurkhiser): Tsdb used to use day buckets, where the end would
# represent a whole day. Snuba queries more accurately thus we must
# capture the entire last day
end = stop + timedelta(days=1)
query = Query(
dataset=Dataset.Outcomes.value,
match=Entity("outcomes"),
select=[
Column("outcome"),
Column("category"),
Function("sum", [Column("quantity")], "total"),
],
where=[
Condition(Column("timestamp"), Op.GTE, start),
Condition(Column("timestamp"), Op.LT, end),
Condition(Column("project_id"), Op.EQ, project.id),
Condition(Column("org_id"), Op.EQ, project.organization_id),
Condition(
Column("outcome"), Op.IN,
[Outcome.ACCEPTED, Outcome.FILTERED, Outcome.RATE_LIMITED]),
Condition(
Column("category"),
Op.IN,
[*DataCategory.error_categories(), DataCategory.TRANSACTION],
),
],
groupby=[Column("outcome"), Column("category")],
granularity=Granularity(ONE_DAY),
)
data = raw_snql_query(query, referrer="reports.outcomes")["data"]
return (
# Accepted errors
sum(row["total"] for row in data
if row["category"] in DataCategory.error_categories()
and row["outcome"] == Outcome.ACCEPTED),
# Dropped errors
sum(row["total"] for row in data
if row["category"] in DataCategory.error_categories()
and row["outcome"] == Outcome.RATE_LIMITED),
# accepted transactions
sum(row["total"] for row in data
if row["category"] == DataCategory.TRANSACTION
and row["outcome"] == Outcome.ACCEPTED),
# Dropped transactions
sum(row["total"] for row in data
if row["category"] == DataCategory.TRANSACTION
and row["outcome"] == Outcome.RATE_LIMITED),
)
def run_outcomes_query_timeseries(query: QueryDefinition) -> ResultSet:
snql_query = Query(
dataset=query.dataset.value,
match=Entity(query.match),
select=query.select_params,
groupby=query.group_by + [Column(TS_COL)],
where=query.conditions,
limit=Limit(10000),
offset=Offset(0),
granularity=Granularity(query.rollup),
)
result_timeseries = raw_snql_query(snql_query, referrer="outcomes.timeseries")
return _format_rows(result_timeseries["data"], query)
def test_orderby(self) -> None:
self.project_id3 = next(self.id_iter)
self.org_id2 = next(self.id_iter)
self.generate_session_events(self.org_id2, self.project_id3)
query = Query(
dataset="sessions",
match=Entity("org_sessions"),
select=[Column("org_id"), Column("project_id")],
groupby=[Column("org_id"), Column("project_id")],
where=[
Condition(Column("started"), Op.GTE,
datetime.utcnow() - timedelta(hours=6)),
Condition(Column("started"), Op.LT, datetime.utcnow()),
],
granularity=Granularity(3600),
orderby=[OrderBy(Column("org_id"), Direction.ASC)],
)
response = self.app.post(
"/sessions/snql",
data=query.snuba(),
)
data = json.loads(response.data)
assert response.status_code == 200, response.data
assert len(data["data"]) == 3
assert data["data"][0]["org_id"] == self.org_id
assert data["data"][0]["project_id"] == self.project_id
assert data["data"][1]["org_id"] == self.org_id
assert data["data"][1]["project_id"] == self.project_id2
assert data["data"][2]["org_id"] == self.org_id2
assert data["data"][2]["project_id"] == self.project_id3
query = query.set_orderby(
[OrderBy(Column("org_id"), Direction.DESC)], )
response = self.app.post(
"/sessions/snql",
data=query.snuba(),
)
data = json.loads(response.data)
assert response.status_code == 200, response.data
assert len(data["data"]) == 3
assert data["data"][0]["org_id"] == self.org_id2
assert data["data"][0]["project_id"] == self.project_id3
assert data["data"][1]["org_id"] == self.org_id
assert data["data"][1]["project_id"] == self.project_id
assert data["data"][2]["org_id"] == self.org_id
assert data["data"][2]["project_id"] == self.project_id2
def _get_snuba_query(
org_id: int,
query: QueryDefinition,
entity_key: EntityKey,
metric_id: int,
columns: Sequence[str],
series: bool,
extra_conditions: List[Condition],
remove_groupby: Set[Column],
) -> Query:
"""Build the snuba query"""
conditions = [
Condition(Column("org_id"), Op.EQ, org_id),
Condition(Column("project_id"), Op.IN,
query.filter_keys["project_id"]),
Condition(Column("metric_id"), Op.EQ, metric_id),
Condition(Column(TS_COL_QUERY), Op.GTE, query.start),
Condition(Column(TS_COL_QUERY), Op.LT, query.end),
]
conditions += _get_filter_conditions(org_id, query.conditions)
conditions += extra_conditions
groupby_tags = [field for field in query.raw_groupby if field != "project"]
tag_keys = {field: _resolve(field) for field in groupby_tags}
groupby = {
field: Column(f"tags[{tag_id}]")
for field, tag_id in tag_keys.items()
if tag_id is not None # exclude unresolved keys from groupby
}
if "project" in query.raw_groupby:
groupby["project"] = Column("project_id")
full_groupby = set(groupby.values()) - remove_groupby
if series:
full_groupby.add(Column(TS_COL_GROUP))
return Query(
dataset=Dataset.Metrics.value,
match=Entity(entity_key.value),
select=[Column(column) for column in columns],
groupby=list(full_groupby),
where=conditions,
granularity=Granularity(query.rollup),
)
def _get_crash_free_rate_data(
org_id: int,
project_ids: Sequence[int],
start: datetime,
end: datetime,
rollup: int,
) -> Dict[int, Dict[str, float]]:
data: Dict[int, Dict[str, float]] = {}
session_status = tag_key(org_id, "session.status")
count_query = Query(
dataset=Dataset.Metrics.value,
match=Entity(EntityKey.MetricsCounters.value),
select=[Column("value")],
where=[
Condition(Column("org_id"), Op.EQ, org_id),
Condition(Column("project_id"), Op.IN, project_ids),
Condition(Column("metric_id"), Op.EQ,
metric_id(org_id, "session")),
Condition(Column("timestamp"), Op.GTE, start),
Condition(Column("timestamp"), Op.LT, end),
],
groupby=[
Column("project_id"),
Column(session_status),
],
granularity=Granularity(rollup),
)
count_data = raw_snql_query(
count_query,
referrer="release_health.metrics.get_crash_free_data",
use_cache=False)["data"]
for row in count_data:
project_data = data.setdefault(row["project_id"], {})
tag_value = reverse_tag_value(org_id, row[session_status])
project_data[tag_value] = row["value"]
return data
def get_oldest_health_data_for_releases(
self,
project_releases: Sequence[ProjectRelease],
) -> Mapping[ProjectRelease, str]:
now = datetime.now(pytz.utc)
start = now - timedelta(days=90)
project_ids: List[ProjectId] = [x[0] for x in project_releases]
org_id = self._get_org_id(project_ids)
release_column_name = tag_key(org_id, "release")
releases = [x[1] for x in project_releases]
releases_ids = [
release_id for release_id in
[try_get_string_index(org_id, release) for release in releases]
if release_id is not None
]
query_cols = [
Column("project_id"),
Column(release_column_name),
Function("min", [Column("bucketed_time")], "oldest"),
]
group_by = [
Column("project_id"),
Column(release_column_name),
]
where_clause = [
Condition(Column("org_id"), Op.EQ, org_id),
Condition(Column("project_id"), Op.IN, project_ids),
Condition(Column("metric_id"), Op.EQ, metric_id(org_id,
"session")),
Condition(Column("timestamp"), Op.GTE, start),
Condition(Column("timestamp"), Op.LT, now),
Condition(Column(release_column_name), Op.IN, releases_ids),
]
query = Query(
dataset=Dataset.Metrics.value,
match=Entity("metrics_counters"),
select=query_cols,
where=where_clause,
groupby=group_by,
granularity=Granularity(3600),
)
rows = raw_snql_query(
query,
referrer=
"release_health.metrics.get_oldest_health_data_for_releases",
use_cache=False,
)["data"]
result = {}
for row in rows:
result[row["project_id"],
reverse_tag_value(org_id, row[release_column_name]
)] = row["oldest"]
return result
groupby=[Column("title")],
where=[
Condition(Column("timestamp"), Op.GT, NOW),
Condition(Function("toHour", [Column("timestamp")]), Op.LTE,
NOW),
Condition(Column("project_id"), Op.IN,
Function("tuple", [1, 2, 3])),
],
having=[
Condition(Function("uniq", [Column("event_id")]), Op.GT, 1)
],
orderby=[OrderBy(Column("title"), Direction.ASC)],
limitby=LimitBy(Column("title"), 5),
limit=Limit(10),
offset=Offset(1),
granularity=Granularity(3600),
totals=Totals(True),
),
(
"MATCH (events SAMPLE 1000)",
"SELECT title, uniq(event_id) AS uniq_events, quantile(0.5)(duration) AS p50",
"BY title",
("WHERE timestamp > toDateTime('2021-01-02T03:04:05.000006') "
"AND toHour(timestamp) <= toDateTime('2021-01-02T03:04:05.000006') "
"AND project_id IN tuple(1, 2, 3)"),
"HAVING uniq(event_id) > 1",
"ORDER BY title ASC",
"LIMIT 5 BY title",
"LIMIT 10",
"OFFSET 1",
"GRANULARITY 3600",
def build_project_series(start__stop, project):
start, stop = start__stop
rollup = ONE_DAY
resolution, series = tsdb.get_optimal_rollup_series(start, stop, rollup)
assert resolution == rollup, "resolution does not match requested value"
clean = partial(clean_series, start, stop, rollup)
def zerofill_clean(data):
return clean(zerofill(data, start, stop, rollup, fill_default=0))
# Note: this section can be removed
issue_ids = project.group_set.filter(status=GroupStatus.RESOLVED,
resolved_at__gte=start,
resolved_at__lt=stop).values_list(
"id", flat=True)
# TODO: The TSDB calls could be replaced with a SnQL call here
tsdb_range_resolved = _query_tsdb_groups_chunked(tsdb.get_range, issue_ids,
start, stop, rollup)
resolved_error_series = reduce(
merge_series,
map(clean, tsdb_range_resolved.values()),
clean([(timestamp, 0) for timestamp in series]),
)
# end
# Use outcomes to compute total errors and transactions
outcomes_query = Query(
dataset=Dataset.Outcomes.value,
match=Entity("outcomes"),
select=[
Column("time"),
Column("category"),
Function("sum", [Column("quantity")], "total"),
],
where=[
Condition(Column("timestamp"), Op.GTE, start),
Condition(Column("timestamp"), Op.LT, stop + timedelta(days=1)),
Condition(Column("project_id"), Op.EQ, project.id),
Condition(Column("org_id"), Op.EQ, project.organization_id),
Condition(Column("outcome"), Op.EQ, Outcome.ACCEPTED),
Condition(
Column("category"),
Op.IN,
[*DataCategory.error_categories(), DataCategory.TRANSACTION],
),
],
groupby=[Column("time"), Column("category")],
granularity=Granularity(rollup),
orderby=[OrderBy(Column("time"), Direction.ASC)],
)
outcome_series = raw_snql_query(outcomes_query,
referrer="reports.outcome_series")
total_error_series = OrderedDict()
for v in outcome_series["data"]:
if v["category"] in DataCategory.error_categories():
timestamp = int(to_timestamp(parse_snuba_datetime(v["time"])))
total_error_series[timestamp] = total_error_series.get(
timestamp, 0) + v["total"]
total_error_series = zerofill_clean(list(total_error_series.items()))
transaction_series = [(int(to_timestamp(parse_snuba_datetime(v["time"]))),
v["total"]) for v in outcome_series["data"]
if v["category"] == DataCategory.TRANSACTION]
transaction_series = zerofill_clean(transaction_series)
error_series = merge_series(
resolved_error_series,
total_error_series,
lambda resolved, total:
(resolved, total - resolved), # Resolved, Unresolved
)
# Format of this series: [(resolved , unresolved, transactions)]
return merge_series(
error_series,
transaction_series,
lambda errors, transactions: errors + (transactions, ),
)
def test_granularity(value: Any, exception: Optional[Exception]) -> None:
if exception is not None:
with pytest.raises(type(exception), match=re.escape(str(exception))):
Granularity(value)
else:
assert Granularity(value).granularity == value
def set_granularity(self, granularity: int) -> "Query":
return self._replace("granularity", Granularity(granularity))
