DAG task scheduler for mesos.
daskos / epos Goto Github PK
View Code? Open in Web Editor NEWWrite DAG Workflows like epic poems via Mesos, Marathon, Chronos, Spark, Dask
Write DAG Workflows like epic poems via Mesos, Marathon, Chronos, Spark, Dask
We use the $MESOS_SANDBOX variable where cloudpickle should reside but when we run our stuff cloudpickle can not be found. The variable and it's content should be checked.
To support the following operations:
odo(spark_dataframe, 'hdfs://path/to/output.parquet')
odo(pandas_dataframe, 'hdfs://path/to/output.parquet')
odo('hdfs://path/to/input.parquet', sqlContext) # spark dataframe
odo('hdfs://path/to/input.parquet', pd.DataFrame) # pandas dataframe
related odo
issue blaze/odo#31
extras_require = {
# TODO revisit
'backends': ['odo', 'pywebhdfs', 'pymongo', 'sqlalchemy', 'paramiko',
'cassandra-driver'],
# dask.mesos should be enough
'mesos': ['dask.mesos', 'satyr', 'toolz', 'mesos.native'],
'spark': ['pyspark', 'py4j']
}
extras_require['complete'] = sorted(set(sum(extras_require.values(), [])))
Programatically call setuptools bdist_egg, and attach to the current spark context.
To support the following conversions:
odo(spark_dataframe, 'cql://cassandrahost::cassandra_table')
odo(pandas_dataframe, 'cql://cassandrahost::cassandra_table')
odo('cql://cassandrahost::cassandra_table', sqlContext) # spark dataframe
odo('cql://cassandrahost::cassandra_table', pd.DataFrame) # pandas dataframe
chronos.py
depends on requests, but it doesn't get installed with setup.py
https://github.com/lensacom/epos/blob/master/epos/context.py#L108
When satyr sends back the result in a queue, it uses cp.dumps and forwards context to the scheduler!
Chunk size can exceed memory limit, to address this we should allow caching partial chunks to disk.
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