def select_sample_sql_barcodes(self, program):
self.log.info('start select %s sql cases' % (program.lower()))
sample_query = 'SELECT case_barcode, sample_barcode FROM %s_metadata_biospecimen' % (
program)
rows = ISBCGC_database_helper.select(self.config,
sample_query,
self.log,
params=[])
sample_case_barcodes = set()
sample_sample_barcodes = set()
duplicates = list()
for row in rows:
case_barcode = row[0].strip()
sample_barcode = row[1].strip()
if sample_barcode in sample_sample_barcodes:
duplicates += [sample_barcode]
sample_case_barcodes.add(case_barcode)
sample_sample_barcodes.add(sample_barcode)
if 0 < len(duplicates):
self.print_partial_list('found sample duplicates', duplicates)
query = 'select l.endpoint_type, c.endpoint_type, count(distinct l.sample_barcode), count(distinct c.sample_barcode) ' \
'from {0}_metadata_biospecimen l left join {0}_metadata_biospecimen c ' \
'on l.sample_barcode = c.sample_barcode ' \
'group by 1, 2'.format(program)
rows = ISBCGC_database_helper.select(self.config,
query,
self.log,
params=[])
self.log.info(
'\nendpoint\tendpoint\tlegacy count\tcurrent count\n%s\n' %
('\n'.join('%s\t%s\t%d\t%d' % (row[0], row[1], row[2], row[3])
for row in rows)))
return sample_sample_barcodes, sample_case_barcodes
def select_clinical_sql_barcodes(self, program):
self.log.info('start select %s sql cases' % (program.lower()))
clinical_query = 'SELECT case_barcode FROM %s_metadata_clinical' % (
program)
rows = ISBCGC_database_helper.select(self.config,
clinical_query,
self.log,
params=[])
clinical_case_barcodes = set()
duplicates = list()
for row in rows:
case_barcode = row[0].strip()
if case_barcode in clinical_case_barcodes:
duplicates += [case_barcode]
# raise ValueError('found duplicate case entry: %s' % (row[0]))
continue
clinical_case_barcodes.add(case_barcode)
if 0 < len(duplicates):
self.print_partial_list('found case duplicates', duplicates)
query = 'select l.endpoint_type, c.endpoint_type, count(distinct l.case_barcode), count(distinct c.case_barcode) ' \
'from {0}_metadata_clinical l left join {0}_metadata_clinical c ' \
'on l.case_barcode = c.case_barcode ' \
'group by 1, 2'.format(program)
rows = ISBCGC_database_helper.select(self.config,
query,
self.log,
params=[])
self.log.info(
'\nendpoint\tendpoint\tlegacy count\tcurrent count\n%s' %
('\n'.join('%s\t%s\t%d\t%d' % (row[0], row[1], row[2], row[3])
for row in rows)))
return clinical_case_barcodes
def process_data_availability_records(config, program, image_config,
image_type, rows, log):
'''
NOTE: this assumes at the start of the run, that no sample barcode is associated with and Image ISB label. it is
possible that a sample_barcode is added and then a subsequent batch will contain that barcode associated with
more files
'''
if 'Radiology' == image_type:
return
stmt = 'select metadata_data_type_availability_id from TCGA_metadata_data_type_availability where %s = isb_label and %s = genomic_build'
image_rows = ISBCGC_database_helper.select(config, stmt, log,
["Pathology_Image", "HG19"])
if 1 != len(image_rows):
raise ValueError(
'unexpected number of rows returned for availability id {}'.format(
image_rows))
data_type_availability_id = image_rows[0][0]
# get the current count for a barcode based on previous runs
stmt = 'select sample_barcode, count(*) from {}_metadata_sample_data_availability where metadata_data_type_availability_id = %s group by 1'.format(
program)
db_rows = ISBCGC_database_helper.select(config, stmt, log, [
data_type_availability_id,
])
db_barcode2count = {}
for db_row in db_rows:
db_barcode2count[db_row[0]] = db_row[1]
if len(db_rows) != len(set(db_rows)):
raise ValueError(
'sample_barcode should only appear once per isb_label')
# get the current count from the current batch for each sample barcode
barcode2count = {}
for row in rows:
barcode2count[row[0]] = barcode2count.setdefault(row[0], 0) + 1
new_barcodes = set(barcode2count) - set(db_rows)
new_params = []
for new_barcode in new_barcodes:
new_params += [[
data_type_availability_id, new_barcode, barcode2count[new_barcode]
]]
ISBCGC_database_helper.column_insert(
config, new_params, 'TCGA_metadata_sample_data_availability',
['metadata_data_type_availability_id', 'sample_barcode', 'count'], log)
update_barcodes = set(barcode2count) & set(db_rows)
update_params = []
for update_barcode in update_barcodes:
update_params += [[
barcode2count[update_barcode] + db_barcode2count[update_barcode],
data_type_availability_id, update_barcode
]]
stmt = 'update TCGA_metadata_sample_data_availability set count = %s where metadata_data_type_availability_id = %s and sample_barcode = %s'
ISBCGC_database_helper.update(config, stmt, log, update_params, False)
def process_biospecimen_image_records(config, program, image_config,
image_type, rows, log):
'''
based on either the sample_barcode (for tissue or diagnostic images),
creates a new metadata clinical record if necessary in the config-specified metadata clinical table
parameters:
config: configuration mappings
image_config: section of the config file with specific mappings for these image types
rows: rows selected from the BigQuery table
log: where to write progress and other messages
endpoint_type: 'legacy'
sample_gdc_id: ?
sample_barcode: row[0]
sample_type: row[0][13:15]
case_gdc_id: ?
case_barcode: row[2]
program_name: 'TCGA'
disease_code: project_name.split('-')[1]
project_short_name: row[4].split('/')[6]
'''
# get the information from the config mapping
log.info('\tchecking biospecimen records')
barcode2row = dict([(row[image_config[image_type]['sample_barcode_index']],
row) for row in rows])
log.info('\tbacodes--{}:{}'.format(len(set(barcode2row)),
len(barcode2row)))
biospecimen_select_template = image_config['biospecimen_select_template']
biospecimen_rows = ISBCGC_database_helper.select(
config,
biospecimen_select_template % ("'" + "','".join(barcode2row) + "'"),
log, [])
barcode_db = set(
[biospecimen_row[0] for biospecimen_row in biospecimen_rows])
new_barcodes = set(barcode2row) - barcode_db
if 0 < len(new_barcodes):
log.info('\t\tinserting {} new biospecimen records'.format(
len(new_barcodes)))
rows = []
for barcode in new_barcodes:
row = barcode2row[barcode]
project_short_name = row[4].split('/')[6]
rows += [[
'legacy', row[0], row[0][13:15], row[2], 'TCGA',
project_short_name.split('-')[1], project_short_name
]]
rows += [[
'current', row[0], row[0][13:15], row[2], 'TCGA',
project_short_name.split('-')[1], project_short_name
]]
ISBCGC_database_helper.column_insert(
config, rows, image_config['biospecimen_table'],
image_config['biospecimen_columns'], log)
else:
log.info('\t\tno rows to insert for biospecimen records')
def main(config_file_name):
log = None
try:
with open(config_file_name) as configFile:
config = json.load(configFile)
log_dir = str(date.today()).replace('-', '_') + '_' + 'ccle/'
log_name = create_log(log_dir, 'update_ccle_gcs_paths')
log = logging.getLogger(log_name)
log.info('begin updating CCLE paths in production')
# first thing to do is to read in the file paths from BigQuery
query = 'SELECT file_gdc_id, file_gcs_url ' \
'FROM [isb-cgc:GDC_metadata.GDCfileID_to_GCSurl] ' \
'where 0 < instr(file_gcs_url, \'CCLE\')'
query_results = query_bq_table(query, True, 'isb-cgc', log)
_, rows, _ = fetch_paged_results(query_results, 2000, None, None, log)
log.info('\tcreate map of filename to path')
name2path = {}
for row in rows:
fields = row[1].split('/')
name2path[fields[-1]] = '/'.join(fields[3:])
log.info('\tfinished map of filename to path')
# get the db rows from production cloudsql
log.info('\tselect ccle filenames from cloudsql')
query = 'SELECT datafilename ' \
'FROM main.metadata_data ' \
'where 0 < instr(datafilename, \'bam\') and project = \'CCLE\''
rows = helper.select(config, query, log, [])
log.info('\tselected %s ccle filenames from cloudsql' % (len(rows)))
# now setup and do the update of paths in cloud sql
log.info('\tstart updating paths in cloudsql')
params = []
not_matched = []
for row in rows:
if row[0] in name2path:
params += [[name2path[row[0]], row[0]]]
else:
not_matched += [row[0]]
update = 'update main.metadata_data set datafilenamekey = %s where datafilename = %s'
helper.update(config, update, log, params)
log.info('\tcompleted update of paths in cloudsql. updated %d, did not find matches from BQ in cloudsql for %s' % (len(params), ', '.join(not_matched)))
log.info('finished updating CCLE paths in production')
except:
if log:
log.exception('failed to update ccle GCS filepaths')
finally:
if log:
close_log(log)
def get_gcs_data_types_barcodes(self, program_name, data_types, log):
log.info('\t\tgetting gcs data types barcodes {}-{} for gcs'.format(
program_name, '"{}"'.format(', '.join(data_types))))
try:
stmt = 'select project_short_name, case_barcode, sample_barcode, file_gdc_id from {} where data_type in ({})'
project2cases = {}
project2samples = {}
project2files = {}
for data_type in data_types:
build = 'HG38' if data_type in ('Aligned Reads', \
'miRNA Expression Quantification', \
'Isoform Expression Quantification', \
'Gene Expression Quantification', \
'Masked Copy Number Segment', \
'Methylation Beta Value', \
'Masked Somatic Mutation') \
else 'HG19'
rows = ISBCGC_database_helper.select(
self.config,
stmt.format(
'{}_metadata_data_{}'.format(program_name, build),
'"{}"'.format(data_type)), log, [])
for row in rows:
cases = project2cases.setdefault(row[0], set())
cases.add(row[1])
samples = project2samples.setdefault(row[0], set())
samples.add(row[2])
files = project2files.setdefault(row[0], set())
files.add(row[3])
log.info(
'\t\tget_gcs_data_types_barcodes(): {}-{} cumulative counts, cases={}, samples={}'
.format(
program_name, data_type,
sum(
len(cases)
for cases in project2cases.itervalues()),
sum(
len(samples)
for samples in project2samples.itervalues())))
log.info(
'\t\tfinished gcs data types barcodes {}-{} for gcs'.format(
program_name, '"{}"'.format(', '.join(data_types))))
return project2cases, project2samples, project2files
except:
log.exception('problem in get_gcs_data_types_barcodes()')
raise
def get_sql_file_info(self, program, barcode_type, barcodes, tag):
barcode2infos = {}
query_template = 'select {0}, data_type, data_format, experimental_strategy, platform, {1}\n' \
'from {2}_metadata_data_HG{3}\n' \
'where {0} in ({4})\n'
barcodes_in = ','.join('"{}"'.format(barcode)
for barcode in set(barcodes))
query = ''
for build in ('19', '38'):
if '38' == build:
if 'CCLE' == program:
break
else:
query += 'union\n'
column = 'analysis_workflow_type'
else:
column = '"None"'
query += query_template.format(barcode_type, column, program,
build, barcodes_in)
rows = ISBCGC_database_helper.select(self.config, query, self.log, [])
for row in rows:
barcode = row[0]
if barcode in barcodes:
barcode2infos[barcode] = barcode2infos.setdefault(
barcode, []) + [[
row[1], row[2],
str(row[3]),
str(row[4]),
str(row[5])
]]
else:
raise ValueError(
'unexpected mismatch of return with barcodes:\n{}\n'.
format(', '.join(barcodes),
', '.join(str(field) for field in row)))
return barcode2infos
def populate_sample_availibility(config, endpt_type, program_name, project_id,
data_type, infos, log):
log.info('\tbegin populate_sample_availibility() for %s:%s' %
(project_id, data_type))
# iterate through the gdc info and put together the counts for the sample barcodes
sample_barcode2count = {}
for info in infos:
mapping = config[program_name]['process_files']['data_table_mapping']
flattened = flatten_map(info, mapping)
for index in range(len(flattened)):
if (data_type in ('Simple somatic mutation', 'Masked Somatic Mutation') and 'controlled ' == flattened[index]['access']) or \
(data_type in ('Aligned reads') and 'open' == flattened[index]['access']):
continue
sample_barcode = flattened[index]['sample_barcode']
count = sample_barcode2count.setdefault(sample_barcode, 0)
sample_barcode2count[sample_barcode] = count + 1
# read in the appropriate data availability row to get the foreign key
isb_label = config['data_type2isb_label'][data_type]
stmt = 'select metadata_data_type_availability_id from %s_metadata_data_type_availability where genomic_build = %%s and isb_label = %%s' % (
program_name)
foreign_key = ISBCGC_database_helper.select(
config, stmt, log,
[config['endpt2genomebuild'][endpt_type], isb_label])[0][0]
params = []
for sample_barcode, count in sample_barcode2count.iteritems():
params += [[foreign_key, sample_barcode, count]]
ISBCGC_database_helper.column_insert(
config, params,
'%s_metadata_sample_data_availability' % (program_name),
['metadata_data_type_availability_id', 'sample_barcode', 'count'], log)
log.info('\tfinished populate_sample_availibility() for %s:%s' %
(project_id, data_type))
def verify_barcodes_filenames(config, program, image_config, image_type, rows,
log):
barcode_bq = set()
if 'Radiology' == image_type:
barcode_bq = set([(row[0], row[1].split('/')[-1]) for row in rows])
else:
barcode_bq = set([(row[0], row[1]) for row in rows])
data_select_template = image_config[image_type][
'data_verify_select_template']
data_rows = ISBCGC_database_helper.select(config, data_select_template,
log, [])
barcode_db = set([(data_row[0], data_row[1]) for data_row in data_rows])
log.info(
'\n\tBQ length:{}\tSQL length:{}\n\tbarcode/file combinations in BQ and not SQL:{}\n\tbarcode/file combinations in SQL and not BQ:{}'
.format(len(barcode_bq), len(barcode_db), len(barcode_bq - barcode_db),
len(barcode_db - barcode_bq)))
if 0 < len(barcode_bq - barcode_db):
log.info('\n\tfirst barcodes in bq only: {}'.format(
list(barcode_bq - barcode_db)[:20]))
if 0 < len(barcode_db - barcode_bq):
log.info('first barcodes in sql only: {}'.format(
list(barcode_db - barcode_bq)[:20]))
def update_database(path2bam2bai, config, log):
log.info('\tbegin update database to match bucket index files')
table2dbpath2bam2bai = {}
for table in ['CCLE_metadata_data_HG19', 'TARGET_metadata_data_HG19', 'TARGET_metadata_data_HG38', 'TCGA_metadata_data_HG19', 'TCGA_metadata_data_HG38']:
program_filenames = call_bigquery(table, log)
dbpath2bam2bai = table2dbpath2bam2bai.setdefault(table, {})
rows = ISBCGC_database_helper.select(config, 'select file_name_key, index_file_name from {} where "BAM" = data_format order by 1'.
format(table), log, [])
log.info('\t\tfound {} rows for {}: {}...{}'.format(len(rows), table, rows[:5], rows[-5:]))
count = 0
print_at = len(rows) / 11
missing_files = set()
bucket2missing_files = {}
mismatchs = 0
bucket2mismatchs = {}
params = []
for row in rows:
if not row[0]:
continue
if 0 == count % print_at:
log.info('\t\t\tlooking at row {} for {}: {}'.format(count, table, row))
count += 1
parts = row[0].split('/')
path = '/'.join(parts[:-1])
bam = parts[-1]
bai = row[1]
bam2bai = path2bam2bai.get(path)
if bam2bai:
assert bam in bam2bai, 'didn\'t find bam {} in tsv files'.format(bam)
if bai != bam2bai[bam]:
mismatchs += 1
curcount = bucket2mismatchs.setdefault(parts[2], 0)
bucket2mismatchs[parts[2]] = curcount + 1
params += [[bam2bai[bam], row[0]]]
else:
missing_files.add(row[0])
curcount = bucket2missing_files.setdefault(parts[2], 0)
bucket2missing_files[parts[2]] = curcount + 1
dbbam2bai = dbpath2bam2bai.setdefault(path, {})
if bam in dbbam2bai:
log.warning('\t\t\tfound {} already in the db map for {}'.format(bam, table))
assert bai, 'didn\'t find a index file for {} in the db'.format(bam)
dbbam2bai[bam] = bai
if 0 < len(params):
# ISBCGC_database_helper.update(config, 'update {} set index_file_name = %s where file_name_key = %s'.format(table), log, params)
log.info('there were {} param sets for update'.format(len(params)))
else:
log.info('there were no param sets for update')
if 0 < len(missing_files):
missing_files = sorted(missing_files)
log.warning('\n\t\t\tfound {} missing files in tsv that are in db out of {} total: \n\t{}\n'.format(len(missing_files), len(rows), '\n\t'.join(missing_files)))
for bucket, bmissing_files in bucket2missing_files.iteritems():
if 0 < bmissing_files:
log.warning('\n\t\t\tfound {} missing files in tsv that is in bucket {}\n'.format(bmissing_files, bucket))
if 0 < mismatchs:
log.warning('\n\t\t\tfound {} index between tsv and db mismatches out of {} total\n'.format(mismatchs, len(rows)))
for bucket, bmismatchs in bucket2mismatchs.iteritems():
if 0 < bmismatchs:
log.warning('\n\t\t\tfound {} mismatches between tsv and db files in bucket {}\n'.format(bmismatchs, bucket))
log.info('\t\tfinished table {}\n\n'.format(table))
log.info('\t\tfind discrepencies in the db from tsv')
for table, dbpath2bam2bai in table2dbpath2bam2bai.iteritems():
bucket2bambai_diff = {}
missing_paths = set()
path2missing_dbfiles = {}
for path, bam2bai in path2bam2bai.iteritems():
if path not in dbpath2bam2bai:
not_curpath = True
for bam in bam2bai:
if bam in program_filenames:
not_curpath = False
break
if not_curpath:
continue
missing_paths.add(path)
continue
dbbam2bai = dbpath2bam2bai[path]
for bam, bai in bam2bai.iteritems():
if bam not in program_filenames:
continue
if bam not in dbbam2bai:
path2missing_dbfiles.setdefault(path, set()).add(bam)
continue
dbbai = dbbam2bai[bam]
if dbbai != bai:
if dbbai.endswith('bam.bai') and bai.endswith('bai'):
bambai_diff = bucket2bambai_diff.setdefault(path.split('/')[2], 0)
bucket2bambai_diff[path.split('/')[2]] = bambai_diff + 1
else:
log.warning('\t\t\tdidn\'t find matching bai in db for table {}: {} vs {}'.format(table, bai, dbbai))
missing_paths = sorted(list(missing_paths))
log.warning('\t\t\tfound {} paths missing from db for table {}: {}...{}\n'.format(len(missing_paths), table, missing_paths[:4], missing_paths[-3:]))
for path, bams in path2missing_dbfiles.iteritems():
bams = sorted(list(bams))
log.warning('\t\t\tfound {} files missing from db for path {} for table {}: {}...{}'.format(len(bams), path, table, bams[:4], bams[-3:]))
log.info('\n\t\t\ttotal of {} files missing from the db that are in the tsv for table {}\n'.format(sum(len(dbfiles) for dbfiles in path2missing_dbfiles.itervalues()), table))
for bucket, bambai_diff in bucket2bambai_diff.iteritems():
if bambai_diff > 0:
log.warning('\t\t\tfound {} cases of \'bai\' in tsv and \'bam.bai\' in db for {} for table {}'.format(bambai_diff, bucket, table))
log.info('\n\t\tfinished discrepancies in the db from tsv')
log.info('\tfinished update database to match bucket index files')
def process_clinical_image_records(config, program, image_config, image_type,
rows, log):
'''
based on either the case_barcode (for radiology images) or the sample_barcode (for tissue or diagnostic images),
creates a new metadata data record in the config-specified metadata data table
parameters:
config: configuration mappings
image_config: section of the config file with specific mappings for these image types
not_barcodes: an output parameter for barcodes that weren't found in the underlying clinical or biospecimen table
rows: rows selected from the BigQuery table
log: where to write progress and other messages
endpoint_type: 'legacy'
case_gdc_id: ?
case_barcode: row[2]
program_name: 'TCGA'
disease_code: project_name.split('-')[1]
project_short_name: row[4].split('/')[6]
'''
# get the information from the config mapping
log.info('\tchecking clinical records.')
barcode2row = dict([(row[image_config[image_type]['case_barcode_index']],
row) for row in rows])
log.info('\tbacodes--{}:{}'.format(len(set(barcode2row)),
len(barcode2row)))
clinical_select_template = image_config['clinical_select_template']
clinical_rows = ISBCGC_database_helper.select(
config,
clinical_select_template % ("'" + "','".join(barcode2row) + "'"), log,
[])
barcode_db = set([clinical_row[0] for clinical_row in clinical_rows])
new_barcodes = set(barcode2row) - barcode_db
if 0 < len(new_barcodes):
log.info('\t\tinserting {} new clinical records'.format(
len(new_barcodes)))
rows = []
for barcode in new_barcodes:
row = barcode2row[barcode]
if 'Radiology' == image_type:
case_barcode = row[0]
project_short_name = row[1].split('/')[5]
else:
case_barcode = row[2]
project_short_name = row[4].split('/')[6]
if 'NA' == project_short_name:
continue
rows += [[
'legacy', case_barcode, program,
project_short_name.split('-')[1], project_short_name
]]
rows += [[
'current', case_barcode, program,
project_short_name.split('-')[1], project_short_name
]]
ISBCGC_database_helper.column_insert(config, rows,
image_config['clinical_table'],
image_config['clinical_columns'],
log)
else:
log.info('\t\tno rows to insert for clinical records')
def process_data_image_records(config, program, image_config, image_type, rows,
log):
'''
based on either the case_barcode (for radiology images) or the sample_barcode (for tissue or diagnostic images),
either updates or creates a new metadata data record in the config-specified metadata data table
parameters:
config: configuration mappings
image_config: section of the config file with specific mappings for these image types
not_barcodes: an output parameter for barcodes that weren't found in the underlying clinical or biospecimen table
rows: rows selected from the BigQuery table
log: where to write progress and other messages
file_gdc_id: ?
case_gdc_id: ?
case_barcode: row[2]
sample_gdc_id: ?
sample_barcode: row[0]
sample_type: sample_barcode[13:15]
aliquot_barcode: row[3]
aliquot_gdc_id: ?
project_short_name: row[4].split('/')[6]
disease_code: project_short_name.split('-')[1]
program_name: 'TCGA'
data_type: image_type
data_category: 'Clinical'
type: 'file'
file_name: row[1]
data_format: 'SVS'
access: 'open'
acl: 'open'
platform: 'Clinical'
file_name_key: row[4]
file_uploaded: 'true'
endpoint_type: 'legacy'
species: 'H**o sapien'
'''
# get the information from the config mapping
log.info('\tchecking data records')
barcode2rows = {}
for row in rows:
if 'Radiology' == image_type:
bcrows = barcode2rows.setdefault((row[0], row[1].split('/')[-1]),
[])
bcrows += [row]
else:
bcrows = barcode2rows.setdefault((row[0], row[1]), [])
bcrows += [row]
data_select_template = image_config[image_type]['data_select_template']
if 0 == len(data_select_template):
barcode_db = set()
else:
barcodes = ''
for barcode, file_name in barcode2rows:
barcodes += '("{}", "{}")'.format(barcode, file_name)
barcodes = barcodes[:-1]
data_rows = ISBCGC_database_helper.select(
config, data_select_template %
(','.join('("{}", "{}")'.format(barcode, file_name)
for barcode, file_name in barcode2rows)), log, [])
barcode_db = set([(data_row[0], data_row[1])
for data_row in data_rows])
new_barcodes = set(barcode2rows) - barcode_db
if 0 < len(new_barcodes):
log.info('\t\tinserting {} new data records'.format(len(new_barcodes)))
db_rows = []
for barcode in new_barcodes:
for row in barcode2rows[barcode]:
row_method = image_config['image_tag2row_method'][image_type]
next_row = getattr(sys.modules[__name__],
row_method)(row, program, image_config,
image_type)
if next_row is not None:
db_rows += next_row
ISBCGC_database_helper.column_insert(
config, db_rows, image_config['data_table'],
image_config[image_type]['data_columns'], log)
else:
log.info('\t\tno rows to insert for data records')
if 0 < len(barcode_db):
log.info('\t\tupdating {} existing data records'.format(
len(barcode_db)))
rows = []
for barcode in barcode_db:
for row in barcode2rows[barcode]:
if 'Radiology' == image_type:
rows += [[
row[1], row[0], row[1].split('/')[5],
image_config['image_tag2data_type'][image_type]
]]
else:
rows += [[
row[4], row[0], row[1],
image_config['image_tag2data_type'][image_type]
]]
ISBCGC_database_helper.update(
config, image_config[image_type]['data_update_template'], log,
rows)
else:
log.info('\t\tno rows to update for data records')
def main(config_file_name):
log = None
try:
with open(config_file_name) as configFile:
config = json.load(configFile)
log_dir = str(date.today()).replace('-', '_') + '_' + 'tcga/'
log_name = create_log(log_dir, 'update_tcga_gcs_paths')
log = logging.getLogger(log_name)
log.info('begin updating TCGA paths in production')
# get the db rows from production cloudsql
log.info('\tselect tcga filenames from cloudsql')
query = 'SELECT datafilename ' \
'FROM metadata_data ' \
'where 0 < instr(datafilename, \'bam\') and project = \'TCGA\''
cloudsql_rows = set(row[0]
for row in helper.select(config, query, log, []))
log.info('\tselected %s tcga filenames from cloudsql' %
(len(cloudsql_rows)))
# read in the file paths from BigQuery
query = 'SELECT file_gdc_id, file_gcs_url ' \
'FROM [isb-cgc:GDC_metadata.GDCfileID_to_GCSurl] ' \
'where 0 < instr(file_gcs_url, \'TCGA\') and 0 < instr(file_gcs_url, \'legacy\') and 0 < instr(file_gcs_url, \'bam\') ' \
'order by file_gcs_url'
query_results = query_bq_table(query, True, 'isb-cgc', log)
total_not_matched = 0
total_distinct = set()
page_token = None
while True:
total_rows, rows, page_token = fetch_paged_results(
query_results, 2000, None, page_token, log)
log.info('\t\tcreate map of filename to path')
name2path = {}
for row in rows:
fields = row[1].split('/')
name2path[fields[-1]] = '/'.join(fields[3:])
log.info('\t\tfinished map of filename to path')
# now setup and do the update of paths in cloud sql
log.info('\t\tstart updating paths in cloudsql')
params = []
select_params = []
not_matched = []
for name, path in name2path.iteritems():
if name in cloudsql_rows:
total_distinct.add(name)
params += [[path, name]]
select_params += [name]
else:
not_matched += [path]
update = 'update metadata_data set datafilenamekey = %s, datafileuploaded = \'true\' where datafilename = %s'
helper.update(config, update, log, params)
select_in = '%s,' * len(select_params)
select_in = select_in[:-1]
select_query = 'select count(*) from metadata_data where datafilename in (%s)' % (
select_in)
count = helper.select(config, select_query, log, select_params)
log.info('select %s file name matches for %s file names.' %
(count[0][0], len(select_params)))
total_not_matched += len(not_matched)
if not page_token:
log.info(
'\t\tupdated total of %s rows for TCGA with %d distinct file names'
% (total_rows - total_not_matched, len(total_distinct)))
break
else:
log.info(
'\t\tupdated %d rows, did not find matches from BQ in cloudsql for %d:\n\t%s'
%
(len(params), len(not_matched), '\n\t'.join(not_matched)))
log.info('\tcompleted update of paths in cloudsql')
log.info('finished updating TCGA paths in production')
except:
if log:
log.exception('failed to update tcga GCS filepaths')
finally:
if log:
close_log(log)