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much faster autotest by grouping in getdata, fixes to getdata to prevent hangs

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This commit is contained in:
John Krauss
2017-03-08 20:51:41 +00:00
parent 6a60cfc417
commit e2f92d78cf
4 changed files with 130 additions and 75 deletions
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149
src/python/test/autotest.py
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@@ -67,38 +67,47 @@ SKIP_COLUMNS = set([
, 'fr.insee.P12_RP_MIBOIS', 'fr.insee.P12_RP_CASE'
, 'fr.insee.P12_RP_TTEGOU', 'fr.insee.P12_RP_ELEC'
, 'fr.insee.P12_ACTOCC15P_ILT45D'
, 'uk.ons.LC3202WA0007'
, 'uk.ons.LC3202WA0010'
, 'uk.ons.LC3202WA0004'
, 'uk.ons.LC3204WA0004'
, 'uk.ons.LC3204WA0007'
, 'uk.ons.LC3204WA0010'
])
MEASURE_COLUMNS = query('''
SELECT ARRAY_AGG(DISTINCT numer_id) numer_ids,
numer_aggregate,
denom_reltype,
section_tags
FROM observatory.obs_meta
WHERE numer_weight > 0
AND numer_id NOT IN ('{skip}')
GROUP BY numer_aggregate, section_tags
AND section_tags IS NOT NULL
AND subsection_tags IS NOT NULL
GROUP BY numer_aggregate, section_tags, denom_reltype
'''.format(skip="', '".join(SKIP_COLUMNS))).fetchall()
CATEGORY_COLUMNS = query('''
SELECT distinct numer_id
FROM observatory.obs_meta
WHERE numer_type ILIKE 'text'
AND numer_weight > 0
''').fetchall()
BOUNDARY_COLUMNS = query('''
SELECT id FROM observatory.obs_column
WHERE type ILIKE 'geometry'
AND weight > 0
''').fetchall()
US_CENSUS_MEASURE_COLUMNS = query('''
SELECT distinct numer_name
FROM observatory.obs_meta
WHERE numer_type ILIKE 'numeric'
AND 'us.census.acs' = ANY (subsection_tags)
AND numer_weight > 0
''').fetchall()
#CATEGORY_COLUMNS = query('''
#SELECT distinct numer_id
#FROM observatory.obs_meta
#WHERE numer_type ILIKE 'text'
#AND numer_weight > 0
#''').fetchall()
#
#BOUNDARY_COLUMNS = query('''
#SELECT id FROM observatory.obs_column
#WHERE type ILIKE 'geometry'
#AND weight > 0
#''').fetchall()
#
#US_CENSUS_MEASURE_COLUMNS = query('''
#SELECT distinct numer_name
#FROM observatory.obs_meta
#WHERE numer_type ILIKE 'numeric'
#AND 'us.census.acs' = ANY (subsection_tags)
#AND numer_weight > 0
#''').fetchall()
#def default_geometry_id(column_id):
@@ -233,53 +242,67 @@ def default_area(column_id):
# assert_is_not_none(rows[0][0])
@parameterized(MEASURE_COLUMNS)
def test_get_measure_points(numer_ids, numer_aggregate, section_tags):
all_in_params = []
def grouped_measure_columns():
for numer_ids, numer_aggregate, denom_reltype, section_tags in MEASURE_COLUMNS:
for colgroup in grouper(numer_ids, 50):
yield [c for c in colgroup if c], numer_aggregate, denom_reltype, section_tags
@parameterized(grouped_measure_columns())
def test_get_measure_points(numer_ids, numer_aggregate, denom_reltype, section_tags):
_test_measures(numer_ids, numer_aggregate, section_tags, denom_reltype, default_point(numer_ids[0]))
@parameterized(grouped_measure_columns())
def test_get_measure_areas(numer_ids, numer_aggregate, denom_reltype, section_tags):
if numer_aggregate.lower() not in ('sum', 'median', 'average'):
return
if numer_aggregate.lower() in ('median', 'average') \
and denom_reltype is not None \
and denom_reltype.lower() != 'universe':
return
_test_measures(numer_ids, numer_aggregate, section_tags, denom_reltype, default_area(numer_ids[0]))
def _test_measures(numer_ids, numer_aggregate, section_tags, denom_reltype, geom):
in_params = []
for numer_id in numer_ids:
all_in_params.append({
in_params.append({
'numer_id': numer_id,
'normalization': 'predenominated'
})
for in_params in grouper(all_in_params, 50):
print('{} {}'.format(numer_aggregate, section_tags))
in_params = [ip for ip in in_params if ip]
params = query(u'''
SELECT {schema}OBS_GetMeta({point}, '{in_params}')
'''.format(schema='cdb_observatory.' if USE_SCHEMA else '',
point=default_point(numer_ids[0]),
in_params=json.dumps(in_params))).fetchone()[0]
try:
# We can get duplicate IDs from multi-denominators
params = OrderedDict([(p['id'], p) for p in params]).values()
assert_equal(len(params), len(in_params))
except:
import pdb
pdb.set_trace()
resp = query(u'''
SELECT * FROM {schema}OBS_GetData(ARRAY[({point}, 1)::geomval], '{params}')
'''.format(schema='cdb_observatory.' if USE_SCHEMA else '',
point=default_point(numer_ids[0]),
params=json.dumps(params).replace(u"'", "''"))).fetchone()[1]
vals = [v['value'] for v in resp]
assert_equal(len(vals), len(in_params))
for i, val in enumerate(vals):
try:
assert_is_not_none(val)
except:
import pdb
pdb.set_trace()
print(val)
raise
#resp = query('''
#SELECT * FROM {schema}OBS_GetMeasure({point}, '{column_id}')
# '''.format(column_id=column_id,
# schema='cdb_observatory.' if USE_SCHEMA else '',
# point=default_point(column_id)))
#rows = resp.fetchall()
#assert_equal(1, len(rows))
#assert_is_not_none(rows[0][0])
params = query(u'''
SELECT {schema}OBS_GetMeta({geom}, '{in_params}')
'''.format(schema='cdb_observatory.' if USE_SCHEMA else '',
geom=geom,
in_params=json.dumps(in_params))).fetchone()[0]
# We can get duplicate IDs from multi-denominators, so for now we
# compress those measures into a single
params = OrderedDict([(p['id'], p) for p in params]).values()
assert_equal(len(params), len(in_params),
'Inconsistent out and in params for {}'.format(in_params))
q = u'''
SELECT * FROM {schema}OBS_GetData(ARRAY[({geom}, 1)::geomval], '{params}')
'''.format(schema='cdb_observatory.' if USE_SCHEMA else '',
geom=geom,
params=json.dumps(params).replace(u"'", "''"))
resp = query(q).fetchone()
#try:
assert_is_not_none(resp, 'NULL returned for {}'.format(in_params))
#except:
# #import pdb
# #pdb.set_trace()
# raise
rawvals = resp[1]
vals = [v['value'] for v in rawvals]
assert_equal(len(vals), len(in_params))
for i, val in enumerate(vals):
assert_is_not_none(val, 'NULL for {}'.format(in_params[i]['numer_id']))
#@parameterized(CATEGORY_COLUMNS)
#def test_get_category_areas(column_id):