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Add support for types in BigQuery #232

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merged 2 commits into from
Jun 27, 2014
Merged

Add support for types in BigQuery #232

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4cb97db
Add support for types in BigQuery
Jun 25, 2014
b2fea7f
Add support for timestamps
Jun 27, 2014
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52 changes: 39 additions & 13 deletions redash/data/query_runner_bigquery.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
import datetime
import httplib2
import json
import logging
Expand All @@ -15,6 +16,38 @@

from redash.utils import JSONEncoder

types_map = {
'INTEGER': 'integer',
'FLOAT': 'float',
'BOOLEAN': 'boolean',
'STRING': 'string',
'TIMESTAMP': 'datetime',
}

def transform_row(row, fields):
column_index = 0
row_data = {}

for cell in row["f"]:
field = fields[column_index]
cell_value = cell['v']

if cell_value is None:
pass
# Otherwise just cast the value
elif field['type'] == 'INTEGER':
cell_value = int(cell_value)
elif field['type'] == 'FLOAT':
cell_value = float(cell_value)
elif field['type'] == 'BOOLEAN':
cell_value = cell_value.lower() == "true"
elif field['type'] == 'TIMESTAMP':
cell_value = datetime.datetime.fromtimestamp(float(cell_value))

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You might want to add support for date/time fields too, otherwise you will have issues with charts.

row_data[field["name"]] = cell_value
column_index += 1

return row_data

def bigquery(connection_string):
def load_key(filename):
Expand Down Expand Up @@ -67,28 +100,21 @@ def query_runner(query):
query_reply = get_query_results(jobs, project_id=project_id,
job_id=insert_response['jobReference']['jobId'], start_index=current_row)

logging.debug("bigquery replied: %s", query_reply)

rows = []
field_names = []
for f in query_reply["schema"]["fields"]:
field_names.append(f["name"])

while ("rows" in query_reply) and current_row < query_reply['totalRows']:
for row in query_reply["rows"]:
row_data = {}
column_index = 0
for cell in row["f"]:
row_data[field_names[column_index]] = cell["v"]
column_index += 1

rows.append(row_data)
rows.append(transform_row(row, query_reply["schema"]["fields"]))

current_row += len(query_reply['rows'])
query_reply = jobs.getQueryResults(projectId=project_id, jobId=query_reply['jobReference']['jobId'],
startIndex=current_row).execute()

columns = [{'name': name,
'friendly_name': name,
'type': None} for name in field_names]
columns = [{'name': f["name"],
'friendly_name': f["name"],
'type': types_map.get(f['type'], "string")} for f in query_reply["schema"]["fields"]]

data = {
"columns": columns,
Expand Down