PyStellarDB 0.0.8

Python interface to StellarDB

PyStellarDB

PyStellarDB is a Python API for executing Transwarp Exetended OpenCypher(TEoC) and Hive query. It could also generate a RDD object which could be used in PySpark. It is base on PyHive(https://github.com/dropbox/PyHive) and PySpark(https://github.com/apache/spark/)

PySpark RDD

We hack a way to generate RDD object using the same method in sc.parallelize(data). It could cause memory panic if the query returns a large amount of data.

Users could use a workaround if you do need huge data: 1. If you are querying a graph, refer to StellarDB manual of Chapter 4.4.5 to save the query data into a temporary table. 2. If you are querying a SQL table, save your query result into a temporary table. 3. Find the HDFS path of the temporary table generated in Step 1 or Step 2. 4. Use API like sc.newAPIHadoopFile() to generate RDD.

Usage

PLAIN Mode (No security is configured)

from pystellardb import stellar_hive

conn = stellar_hive.StellarConnection(host="localhost", port=10000, graph_name='pokemon')
cur = conn.cursor()
cur.execute('config query.lang cypher')
cur.execute('use graph pokemon')
cur.execute('match p = (a)-[f]->(b) return a,f,b limit 1')

print cur.fetchall()

LDAP Mode

from pystellardb import stellar_hive

conn = stellar_hive.StellarConnection(host="localhost", port=10000, username='hive', password='123456', auth='LDAP', graph_name='pokemon')
cur = conn.cursor()
cur.execute('config query.lang cypher')
cur.execute('use graph pokemon')
cur.execute('match p = (a)-[f]->(b) return a,f,b limit 1')

print cur.fetchall()

Kerberos Mode

# Make sure you have the correct realms infomation about the KDC server in /etc/krb5.conf
# Make sure you have the correct keytab file in your environment
# Run kinit command:
# In Linux: kinit -kt FILE_PATH_OF_KEYTABL PRINCIPAL_NAME
# In Mac: kinit -t FILE_PATH_OF_KEYTABL -f PRINCIPAL_NAME

from pystellardb import stellar_hive

conn = stellar_hive.StellarConnection(host="localhost", port=10000, kerberos_service_name='hive', auth='KERBEROS', graph_name='pokemon')
cur = conn.cursor()
cur.execute('config query.lang cypher')
cur.execute('use graph pokemon')
cur.execute('match p = (a)-[f]->(b) return a,f,b limit 1')

print cur.fetchall()

Execute Hive Query

from pystellardb import stellar_hive

# If `graph_name` parameter is None, it will execute a Hive query and return data just as PyHive does
conn = stellar_hive.StellarConnection(host="localhost", port=10000, database='default')
cur = conn.cursor()
cur.execute('SELECT * FROM default.abc limit 10')

Execute Graph Query and change to a PySpark RDD object

from pyspark import SparkContext
from pystellardb import stellar_hive

sc = SparkContext("local", "Demo App")

conn = stellar_hive.StellarConnection(host="localhost", port=10000, graph_name='pokemon')
cur = conn.cursor()
cur.execute('config query.lang cypher')
cur.execute('use graph pokemon')
cur.execute('match p = (a)-[f]->(b) return a,f,b limit 10')

rdd = cur.toRDD(sc)

def f(x): print(x)

rdd.map(lambda x: (x[0].toJSON(), x[1].toJSON(), x[2].toJSON())).foreach(f)

# Every line of this query is in format of Tuple(VertexObject, EdgeObject, VertexObject)
# Vertex and Edge object has a function of toJSON() which can print the object in JSON format

Execute Hive Query and change to a PySpark RDD object

from pyspark import SparkContext
from pystellardb import stellar_hive

sc = SparkContext("local", "Demo App")

conn = stellar_hive.StellarConnection(host="localhost", port=10000)
cur = conn.cursor()
cur.execute('select * from default_db.default_table limit 10')

rdd = cur.toRDD(sc)

def f(x): print(x)

rdd.foreach(f)

# Every line of this query is in format of Tuple(Column, Column, Column)

Dependencies

Required:

• Python 2.7+ / Python 3

System SASL

Different systems require different packages to be installed to enable SASL support in Impyla. Some examples of how to install the packages on different distributions follow.

Ubuntu:

apt-get install libsasl2-dev libsasl2-2 libsasl2-modules-gssapi-mit
apt-get install python-dev gcc              #Update python and gcc if needed

RHEL/CentOS:

yum install cyrus-sasl-md5 cyrus-sasl-plain cyrus-sasl-gssapi cyrus-sasl-devel
yum install gcc-c++ python-devel.x86_64     #Update python and gcc if needed

Requirements

Install using

• pip install 'pystellardb[hive]' for the Hive interface.

PyHive works with

• For Hive: HiveServer2 daemon

Testing

On his way