def _get_logger(run_local, tag):
try:
return PipelineStreamLogger(staticconf.read_string("log_stream_name"),
run_local, tag)
except:
logger.write_msg("Error creating a pipeline stream logger!")
return logger # Return existing logger instance in case of errors
def test_pipeline_json():
logger = PipelineStreamLogger(None, False, 'test')
now = time.time()
js = logger._pipeline_json('complete',
error_msg='error!',
extra_msg='extra',
job_start_secs=now)
json_dict = simplejson.loads(js)
assert json_dict['msg']['status'] == 'complete'
assert json_dict['msg']['additional_info'] == 'extra'
# if the above lines of code take longer than 10 seconds something's wrong
assert json_dict['msg']['job_time'] < 10
assert json_dict['tag'] == 'test'
def rs_check_schema(rs_mgmt, args):
yaml_data = load_from_file(args.schema)
tables = RedShiftLogSchema(safe_load(yaml_data)).tables()
db = read_string('pipeline.redshift_database')
log_stream = read_string('pipeline.load_step.s3_to_redshift_stream')
pipe_strm_lgr = PipelineStreamLogger(
log_stream,
True,
'rs_check_schema'
)
psql = RedshiftPostgres(pipe_strm_lgr, args.credentials, run_local=True)
rs_check_table_def(psql, db, tables, args.redshift_schema)
rs_check_table_rows(psql, db, tables, args.redshift_schema)
def s3_to_psv_main(args):
mrjob = read_string('pipeline.et_step.mrjob')
stream_name = read_string('pipeline.et_step.s3_to_s3_stream')
DATABASE = read_string('pipeline.redshift_database')
LOG_STREAM = PipelineStreamLogger(stream_name,
args.run_local,
mrjob,
input_date=args.date)
day_to_run = setup_dates_to_check(args.date, args.run_local, LOG_STREAM)
try:
if not args.run_local:
setup_private(args.private)
# Create a psql instance based on args
if args.skip_progress_in_redshift:
status_table = DynamoDbStatusTable(LOG_STREAM,
run_local=args.run_local)
else:
status_table = RedshiftStatusTable(
RedshiftPostgres(LOG_STREAM,
args.private,
run_local=args.run_local))
load_msg = __load_data_from_s3(
status_table,
read_list('pipeline.et_step.s3_prefixes'),
day_to_run,
mrjob,
args.run_local,
DATABASE,
LOG_STREAM,
force_et=args.force_et)
LOG_STREAM.write_msg("complete", extra_msg=load_msg)
finally:
clear_env(args.run_local)
def test_handle_error(input_value):
test_logger = PipelineStreamLogger("test_stream", False, "test_tag")
with pytest.raises(Exception):
handle_error(input_value, test_logger)
def s3_to_redshift_main(args):
db = read_string('pipeline.redshift_database')
s3_log_prefix = read_string('pipeline.s3_output_prefix').format(
logname=os.environ.get('LOGNAME', 'unknown'))
# setup logging
stream_name = read_string('pipeline.load_step.s3_to_redshift_stream')
LOG_STREAM = PipelineStreamLogger(stream_name,
args.run_local,
's3_to_redshift',
job_name='load')
# handle to redshift db
loader_psql = RedshiftPostgres(LOG_STREAM,
args.private,
run_local=args.run_local)
if args.skip_progress_in_redshift:
status_table = DynamoDbStatusTable(LOG_STREAM,
run_local=args.run_local)
else:
status_table = RedshiftStatusTable(loader_psql)
create_tuples = get_table_creates(args.db_file, LOG_STREAM)
data_candidates = dates_from_rs_status(
status_table,
db,
LOG_STREAM,
args.retry_errors,
args.date,
)
if data_candidates:
try:
update_database_schema(loader_psql, db, data_candidates[0],
s3_log_prefix, args.db_file, LOG_STREAM)
except Exception as e:
status_table.update_status(db,
data_candidates[0],
get_yaml_table_versions(
pipeline_yaml_schema_file_path()),
"error",
start_time_secs=time.time(),
error_msg=repr(e))
raise
elif args.date is not None:
raise IOError("{0} data is either already loaded \
or has not yet completed ET step".format(args.date))
logs_to_copy = []
for input_date in data_candidates:
LOG_STREAM = PipelineStreamLogger(stream_name,
args.run_local,
's3_to_redshift',
job_name='load',
input_date=input_date)
logs_to_copy = [(join(s3_log_prefix, input_date, table), table)
for (table, _) in create_tuples]
copy_tables(loader_psql, status_table, db, input_date, logs_to_copy,
args.ttl_days, LOG_STREAM)
def analyze_tables(psql, db, tables, schemaname=DEFAULT_NAMESPACE):
num_failures = 0
for tbl_name in tables:
tbl_name = get_namespaced_tablename(tbl_name, schemaname)
try:
analyze_table(psql, db, tbl_name)
except:
num_failures += 1
if num_failures:
raise RuntimeError(
'failed to analyze {0} tables, see log'.format(num_failures))
if __name__ == "__main__":
args = get_cmd_line_args()
run_local = args.run_local
merge_configs(args.config)
db = read_string('pipeline.redshift_database')
log_stream = read_string('pipeline.load_step.s3_to_redshift_stream')
logstream = PipelineStreamLogger(log_stream, run_local, 'redshift_maint')
psql = RedshiftPostgres(logstream, args.credentials, run_local=run_local)
yaml = load_from_file(args.schema)
schema = RedShiftLogSchema(safe_load(yaml))
if args.compact:
compact_tables(psql, db, schema.tables(), args.redshift_schema)
analyze_tables(psql, db, schema.tables(), args.redshift_schema)