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POin python: child processes going defunct while others are not, unsure why
 

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  1. POin python: child processes going defunct while others are not, unsure why
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    <p>edit: the answer was that the os was axing processes because i was consuming all the memory</p> <p>i am spawning enough subprocesses to keep the load average 1:1 with cores, however at some point within the hour, this script could run for days, 3 of the processes go :</p> <pre><code>tipu 14804 0.0 0.0 328776 428 pts/1 Sl 00:20 0:00 python run.py tipu 14808 64.4 24.1 2163796 1848156 pts/1 Rl 00:20 44:41 python run.py tipu 14809 8.2 0.0 0 0 pts/1 Z 00:20 5:43 [python] &lt;defunct&gt; tipu 14810 60.3 24.3 2180308 1864664 pts/1 Rl 00:20 41:49 python run.py tipu 14811 20.2 0.0 0 0 pts/1 Z 00:20 14:04 [python] &lt;defunct&gt; tipu 14812 22.0 0.0 0 0 pts/1 Z 00:20 15:18 [python] &lt;defunct&gt; tipu 15358 0.0 0.0 103292 872 pts/1 S+ 01:30 0:00 grep python </code></pre> <p>i have no idea why this is happening, attached is the master and slave. i can attach the mysql/pg wrappers if needed as well, any suggestions?</p> <p><code>slave.py</code>:</p> <pre><code>from boto.s3.key import Key import multiprocessing import gzip import os from mysql_wrapper import MySQLWrap from pgsql_wrapper import PGSQLWrap import boto import re class Slave: CHUNKS = 250000 BUCKET_NAME = "bucket" AWS_ACCESS_KEY = "" AWS_ACCESS_SECRET = "" KEY = Key(boto.connect_s3(AWS_ACCESS_KEY, AWS_ACCESS_SECRET).get_bucket(BUCKET_NAME)) S3_ROOT = "redshift_data_imports" COLUMN_CACHE = {} DEFAULT_COLUMN_VALUES = {} def __init__(self, job_queue): self.log_handler = open("logs/%s" % str(multiprocessing.current_process().name), "a"); self.mysql = MySQLWrap(self.log_handler) self.pg = PGSQLWrap(self.log_handler) self.job_queue = job_queue def do_work(self): self.log(str(os.getpid())) while True: #sample job in the abstract: mysql_db.table_with_date-iteration job = self.job_queue.get() #queue is empty if job is None: self.log_handler.close() self.pg.close() self.mysql.close() print("good bye and good day from %d" % (os.getpid())) self.job_queue.task_done() break #curtail iteration table = job.split('-')[0] #strip redshift table from job name redshift_table = re.sub(r"(_[1-9].*)", "", table.split(".")[1]) iteration = int(job.split("-")[1]) offset = (iteration - 1) * self.CHUNKS #columns redshift is expecting #bad tables will slip through and error out, so we catch it try: colnames = self.COLUMN_CACHE[redshift_table] except KeyError: self.job_queue.task_done() continue #mysql fields to use in SELECT statement fields = self.get_fields(table) #list subtraction determining which columns redshift has that mysql does not delta = (list(set(colnames) - set(fields.keys()))) #subtract columns that have a default value and so do not need padding if delta: delta = list(set(delta) - set(self.DEFAULT_COLUMN_VALUES[redshift_table])) #concatinate columns with padded \N select_fields = ",".join(fields.values()) + (",\\N" * len(delta)) query = "SELECT %s FROM %s LIMIT %d, %d" % (select_fields, table, offset, self.CHUNKS) rows = self.mysql.execute(query) self.log("%s: %s\n" % (table, len(rows))) if not rows: self.job_queue.task_done() continue #if there is more data potentially, add it to the queue if len(rows) == self.CHUNKS: self.log("putting %s-%s" % (table, (iteration+1))) self.job_queue.put("%s-%s" % (table, (iteration+1))) #various characters need escaping clean_rows = [] redshift_escape_chars = set( ["\\", "|", "\t", "\r", "\n"] ) in_chars = "" for row in rows: new_row = [] for value in row: if value is not None: in_chars = str(value) else: in_chars = "" #escape any naughty characters new_row.append("".join(["\\" + c if c in redshift_escape_chars else c for c in in_chars])) new_row = "\t".join(new_row) clean_rows.append(new_row) rows = ",".join(fields.keys() + delta) rows += "\n" + "\n".join(clean_rows) offset = offset + self.CHUNKS filename = "%s-%s.gz" % (table, iteration) self.move_file_to_s3(filename, rows) self.begin_data_import(job, redshift_table, ",".join(fields.keys() + delta)) self.job_queue.task_done() def move_file_to_s3(self, uri, contents): tmp_file = "/dev/shm/%s" % str(os.getpid()) self.KEY.key = "%s/%s" % (self.S3_ROOT, uri) self.log("key is %s" % self.KEY.key ) f = gzip.open(tmp_file, "wb") f.write(contents) f.close() #local saving allows for debugging when copy commands fail #text_file = open("tsv/%s" % uri, "w") #text_file.write(contents) #text_file.close() self.KEY.set_contents_from_filename(tmp_file, replace=True) def get_fields(self, table): """ Returns a dict used as: {"column_name": "altered_column_name"} Currently only the debug column gets altered """ exclude_fields = ["_qproc_id", "_mob_id", "_gw_id", "_batch_id", "Field"] query = "show columns from %s" % (table) fields = self.mysql.execute(query) #key raw field, value mysql formatted field new_fields = {} #for field in fields: for field in [val[0] for val in fields]: if field in exclude_fields: continue old_field = field if "debug_mode" == field.strip(): field = "IFNULL(debug_mode, 0)" new_fields[old_field] = field return new_fields def log(self, text): self.log_handler.write("\n%s" % text) def begin_data_import(self, table, redshift_table, fields): query = "copy %s (%s) from 's3://bucket/redshift_data_imports/%s' \ credentials 'aws_access_key_id=%s;aws_secret_access_key=%s' delimiter '\\t' \ gzip NULL AS '' COMPUPDATE ON ESCAPE IGNOREHEADER 1;" \ % (redshift_table, fields, table, self.AWS_ACCESS_KEY, self.AWS_ACCESS_SECRET) self.pg.execute(query) </code></pre> <p><code>master.py</code>:</p> <pre><code>from slave import Slave as Slave import multiprocessing from mysql_wrapper import MySQLWrap as MySQLWrap from pgsql_wrapper import PGSQLWrap as PGSQLWrap class Master: SLAVE_COUNT = 5 def __init__(self): self.mysql = MySQLWrap() self.pg = PGSQLWrap() def do_work(table): pass def get_table_listings(self): """Gathers a list of MySQL log tables needed to be imported""" query = 'show databases' result = self.mysql.execute(query) #turns list[tuple] into a flat list databases = list(sum(result, ())) #overriding during development databases = ['db1', 'db2', 'db3']] exclude = ('mysql', 'Database', 'information_schema') scannable_tables = [] for database in databases: if database in exclude: continue query = "show tables from %s" % database result = self.mysql.execute(query) #turns list[tuple] into a flat list tables = list(sum(result, ())) for table in tables: exclude = ("Tables_in_%s" % database, "(", "201303", "detailed", "ltv") #exclude any of the unfavorables if any(s in table for s in exclude): continue scannable_tables.append("%s.%s-1" % (database, table)) return scannable_tables def init(self): #fetch redshift columns once and cache #get columns from redshift so we can pad the mysql column delta with nulls tables = ('table1', 'table2', 'table3') for table in tables: #cache columns query = "SELECT column_name FROM information_schema.columns WHERE \ table_name = '%s'" % (table) result = self.pg.execute(query, async=False, ret=True) Slave.COLUMN_CACHE[table] = list(sum(result, ())) #cache default values query = "SELECT column_name FROM information_schema.columns WHERE \ table_name = '%s' and column_default is not \ null" % (table) result = self.pg.execute(query, async=False, ret=True) #turns list[tuple] into a flat list result = list(sum(result, ())) Slave.DEFAULT_COLUMN_VALUES[table] = result def run(self): self.init() job_queue = multiprocessing.JoinableQueue() tables = self.get_table_listings() for table in tables: job_queue.put(table) processes = [] for i in range(Master.SLAVE_COUNT): process = multiprocessing.Process(target=slave_runner, args=(job_queue,)) process.daemon = True process.start() processes.append(process) #blocks this process until queue reaches 0 job_queue.join() #signal each child process to GTFO for i in range(Master.SLAVE_COUNT): job_queue.put(None) #blocks this process until queue reaches 0 job_queue.join() job_queue.close() #do not end this process until child processes close out for process in processes: process.join() #toodles ! print("this is master saying goodbye") def slave_runner(queue): slave = Slave(queue) slave.do_work() </code></pre>
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    1. PO
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      1. PTAnswer
    1. This table or related slice is empty.
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    1. UStipu
    plurals
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. PO
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      1. POin python: child processes going defunct while others are not, unsure why
      1. UStipu
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    1. COHave you looked at the logs or the stdout or stderr? In particular, are the children quitting because of an unhandled exception? (If you use `multiprocessing.Pool`, that's taken care of for you. If you build one yourself, you have to write the code to take care of it.)
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      1. POin python: child processes going defunct while others are not, unsure why
      1. USabarnert
    2. COFor that matter… it looks like you're trying to build almost _exactly_ the same thing as `Pool`. Why not just use `Pool` instead? (You could then simplify and/or optimize things even further by using one of the `map`-family methods on the `Pool` over `tables`.)
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      1. POin python: child processes going defunct while others are not, unsure why
      1. USabarnert
    3. CO@abarnert because the workload isn't generated once in the beginning, it is dynamically expanded upon on a per table basis.
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      1. POin python: child processes going defunct while others are not, unsure why
      1. UStipu
 

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