def top_tables(request):
response = {'status': -1}
database = request.POST.get('database', 'default')
limit = request.POST.get('len', 1000)
api = OptimizerApi(user=request.user)
data = api.top_tables(database_name=database, page_size=limit)
tables = [{
'eid': table['eid'],
'database': _get_table_name(table['name'])['database'],
'name': _get_table_name(table['name'])['table'],
'popularity': table['workloadPercent'],
'column_count': table['columnCount'],
'patternCount': table['patternCount'],
'total': table['total'],
'is_fact': table['type'] != 'Dimension'
} for table in data['results']
]
response['top_tables'] = tables
response['status'] = 0
return JsonResponse(response)
def upload_table_stats(request):
response = {'status': -1}
db_tables = json.loads(request.POST.get('db_tables'), '[]')
source_platform = request.POST.get('sourcePlatform', 'hive')
with_columns = json.loads(request.POST.get('with_columns', 'false'))
with_ddl = json.loads(request.POST.get('with_ddl', 'false'))
table_stats = []
column_stats = []
table_ddls = []
for db_table in db_tables:
path = _get_table_name(db_table)
try:
if with_ddl:
db = dbms.get(request.user)
query = hql_query('SHOW CREATE TABLE `%(database)s`.`%(table)s`' % path)
handle = db.execute_and_wait(query, timeout_sec=5.0)
if handle:
result = db.fetch(handle, rows=5000)
db.close(handle)
table_ddls.append((0, 0, ' '.join([row[0] for row in result.rows()]), path['database']))
full_table_stats = json.loads(get_table_stats(request, database=path['database'], table=path['table']).content)
stats = dict((stat['data_type'], stat['comment']) for stat in full_table_stats['stats'])
table_stats.append({
'table_name': path['table'],
'num_rows': stats.get('numRows', -1),
'last_modified_time': stats.get('transient_lastDdlTime', -1),
'total_size': stats.get('totalSize', -1),
'raw_data_size': stats.get('rawDataSize', -1),
'num_files': stats.get('numFiles', -1),
# bytes_cached
# cache_replication
# format
})
if with_columns:
for col in full_table_stats['columns']:
col_stats = json.loads(get_table_stats(request, database=path['database'], table=path['table'], column=col).content)['stats']
col_stats = dict([(key, val) for col_stat in col_stats for key, val in col_stat.iteritems()])
column_stats.append({
'table_name': path['table'],
'column_name': col,
'data_type': col_stats['data_type'],
"num_distinct": int(col_stats.get('distinct_count')) if col_stats.get('distinct_count') != '' else -1,
"num_nulls": int(col_stats['num_nulls']) if col_stats['num_nulls'] != '' else -1,
"avg_col_len": int(float(col_stats['avg_col_len'])) if col_stats['avg_col_len'] != '' else -1,
"max_size": int(float(col_stats['max_col_len'])) if col_stats['max_col_len'] != '' else -1,
"min": col_stats['min'] if col_stats.get('min', '') != '' else -1,
"max": col_stats['max'] if col_stats.get('max', '') != '' else -1,
"num_trues": col_stats['num_trues'] if col_stats.get('num_trues', '') != '' else -1,
"num_falses": col_stats['num_falses'] if col_stats.get('num_falses', '') != '' else -1,
})
except Exception, e:
LOG.exception('Skipping upload of %s: %s' % (db_table, e))
def upload_table_stats(request):
response = {'status': -1}
db_tables = json.loads(request.POST.get('db_tables'), '[]')
source_platform = json.loads(request.POST.get('sourcePlatform', '"hive"'))
with_ddl = json.loads(request.POST.get('with_ddl', 'false'))
with_table_stats = json.loads(request.POST.get('with_table', 'false'))
with_columns_stats = json.loads(request.POST.get('with_columns', 'false'))
table_ddls = []
table_stats = []
column_stats = []
if not OPTIMIZER.AUTO_UPLOAD_DDL.get():
with_ddl = False
if not OPTIMIZER.AUTO_UPLOAD_STATS.get():
with_table_stats = with_columns_stats = False
for db_table in db_tables:
path = _get_table_name(db_table)
try:
if with_ddl:
db = _get_db(request.user, source_type=source_platform)
query = hql_query('SHOW CREATE TABLE `%(database)s`.`%(table)s`' % path)
handle = db.execute_and_wait(query, timeout_sec=5.0)
if handle:
result = db.fetch(handle, rows=5000)
db.close(handle)
table_ddls.append((0, 0, ' '.join([row[0] for row in result.rows()]), path['database']))
if with_table_stats:
mock_request = MockRequest(user=request.user, source_platform=source_platform)
full_table_stats = json.loads(get_table_stats(mock_request, database=path['database'], table=path['table']).content)
stats = dict((stat['data_type'], stat['comment']) for stat in full_table_stats['stats'])
table_stats.append({
'table_name': '%(database)s.%(table)s' % path, # DB Prefix
'num_rows': stats.get('numRows', -1),
'last_modified_time': stats.get('transient_lastDdlTime', -1),
'total_size': stats.get('totalSize', -1),
'raw_data_size': stats.get('rawDataSize', -1),
'num_files': stats.get('numFiles', -1),
'num_partitions': stats.get('numPartitions', -1),
# bytes_cached
# cache_replication
# format
})
if with_columns_stats:
if source_platform == 'impala':
colum_stats = json.loads(get_table_stats(mock_request, database=path['database'], table=path['table'], column=-1).content)['stats']
else:
colum_stats = [
json.loads(get_table_stats(mock_request, database=path['database'], table=path['table'], column=col).content)['stats']
for col in full_table_stats['columns'][:25]
]
raw_column_stats = [dict([(key, val if val is not None else '') for col_stat in col for key, val in col_stat.iteritems()]) for col in colum_stats]
for col_stats in raw_column_stats:
column_stats.append({
'table_name': '%(database)s.%(table)s' % path, # DB Prefix
'column_name': col_stats['col_name'],
'data_type': col_stats['data_type'],
"num_distinct": int(col_stats.get('distinct_count')) if col_stats.get('distinct_count') != '' else -1,
"num_nulls": int(col_stats['num_nulls']) if col_stats['num_nulls'] != '' else -1,
"avg_col_len": int(float(col_stats['avg_col_len'])) if col_stats['avg_col_len'] != '' else -1,
"max_size": int(float(col_stats['max_col_len'])) if col_stats['max_col_len'] != '' else -1,
"min": col_stats['min'] if col_stats.get('min', '') != '' else -1,
"max": col_stats['max'] if col_stats.get('max', '') != '' else -1,
"num_trues": col_stats['num_trues'] if col_stats.get('num_trues', '') != '' else -1,
"num_falses": col_stats['num_falses'] if col_stats.get('num_falses', '') != '' else -1,
})
except Exception, e:
LOG.exception('Skipping upload of %s: %s' % (db_table, e))
