Last active
December 11, 2015 13:38
-
-
Save jeremykarn/4608709 to your computer and use it in GitHub Desktop.
The Pig and Python scripts for a Mortar web project that generates the MongoLoader schema associated with a Mongo collection. Need to supply your own MongoDB connection details and your own s3 bucket.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# | |
# Copyright 2012 Mortar Data Inc. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
PIG CODE: | |
data = LOAD 'mongodb://<user>:<password>@<host>:<port>/<database_name>.<collection_name>' USING com.mongodb.hadoop.pig.MongoLoader(); | |
raw_fields = FOREACH data GENERATE flatten(mongo_map(document)); | |
key_type_groups = GROUP raw_fields BY (keyname, type); | |
key_type_counts = FOREACH key_type_groups GENERATE flatten(group), COUNT(raw_fields.keyname) as count:long; | |
name_groups = GROUP key_type_counts BY keyname; | |
all_keys = GROUP name_groups all; | |
out = FOREACH all_keys { | |
results = ORDER name_groups BY group; | |
GENERATE create_mongo_schema(results); | |
} | |
rmf s3n://<your_s3_bucket>/schema_out; | |
STORE out INTO 's3n://<your_s3_bucket>/schema_out' USING PigStorage('\t'); | |
PYTHON CODE: | |
@outputSchema('mongo_data:bag{t:(keyname:chararray, type:chararray, val:chararray)}') | |
def mongo_map(d, prefix=""): | |
""" | |
Go through a dictionary and for every key record the key name, type, and data value. | |
Recursively goes through embedded lists/dictionaries and prepends parent keys to the key name. | |
""" | |
output = [] | |
for k,v in d.iteritems(): | |
key_name = "%s%s" % (prefix, k) | |
if type(v) == list: | |
output.append( (key_name, type(v).__name__, type(v).__name__) ) | |
for t in v: | |
for t_item in t: | |
if type(t_item) == dict: | |
output += mongo_map(t_item, "%s." % key_name) | |
elif type(v) == dict: | |
output.append( (key_name, type(v).__name__, type(v).__name__) ) | |
output += mongo_map(v, "%s." % key_name) | |
else: | |
#For simple types, keep example values | |
output.append( (key_name, type(v).__name__, "%s" % v) ) | |
return output | |
@outputSchema('schema:chararray') | |
def create_mongo_schema(results, prefix_to_remove=""): | |
""" | |
Create a schema string that can be used by the MongoLoader for this collection. | |
results: List of keyname with ordered counts of the type: | |
[ (keyname, [ (type1, count1), (type2, count2) ]), | |
(keyname, [ (type1, count1), (type2, count2) ]), ... ] | |
prefix_to_remove: String to remove from keyname. | |
""" | |
params = [] | |
index = 0 | |
while index < len(results): | |
t = results[index] | |
full_key_name = t[0] | |
short_key_name = t[0].replace(prefix_to_remove, "") | |
key_type_counts = t[1] | |
key_type_counts.sort(key=lambda x: x[1]) | |
key_type = key_type_counts[0][1] | |
if key_type == 'NoneType': | |
if len(key_type_counts) > 1: | |
key_type = key_type_counts[1][1] | |
else: | |
#Default to loading field as a string | |
key_type = "unicode" | |
if key_type == 'list': | |
inner_params = [] | |
index += 1 | |
while index < len(results) and results[index][0].startswith(full_key_name): | |
inner_params.append(results[index]) | |
index += 1 | |
inner_schema = create_mongo_schema(inner_params, "%s%s." % (prefix_to_remove, short_key_name)) | |
param = "%s:bag{t:tuple(%s)}" % (short_key_name, inner_schema) | |
elif key_type == 'dict': | |
inner_params = [] | |
index += 1 | |
while index < len(results) and results[index][0].startswith(full_key_name): | |
inner_params.append(results[index]) | |
index += 1 | |
inner_schema = create_mongo_schema(inner_params, "%s%s." % (prefix_to_remove, short_key_name)) | |
param = "%s:tuple(%s)" % (short_key_name, inner_schema) | |
else: | |
pig_key_type = _get_pig_type(key_type) | |
param = "%s:%s" % (short_key_name, pig_key_type) | |
index += 1 | |
params.append(param) | |
schema = ",".join(params) | |
#Print out final schema but not intermediate ones | |
if not prefix_to_remove: | |
print schema | |
return schema | |
def _get_pig_type(python_type): | |
if python_type == 'unicode': | |
return 'chararray' | |
elif python_type == 'bytearray': | |
return 'bytearray' | |
elif python_type == 'long': | |
return 'long' | |
elif python_type == 'int': | |
return 'int' | |
elif python_type == 'float': | |
return 'double' | |
else: | |
return 'unknown' | |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment