How to create dataframe in pyspark using odbc - pyspark

Need to create a dataframe.
Using pyspark or spark.
No use of pandas.
I m using odbc connection.

Related

How to read tables from synapse database tables using pyspark

I am a newbie to Azure Synapse, I have to work on the Azure spark notebook. One of my colleagues connected the on-prime database using the azure link service. Now I have written a test framework for comparing the on-prime data and data-lake(curated) data. but I don't understand how to read those tables using Pyspark.
here is my linked service data structure.
enter image description here
here my Link service names and Database name.
You can read any file as a table which is stored in Synapse Linked location by using Azure Synapse Dedicated SQL Pool Connector for Apache Spark.
First you need to read the file which you need to read as the table in Synapse. Use below code to read the file.
%%pyspark
df = spark.read.load('abfss://sampleadls2#sampleadls1.dfs.core.windows.net/business.csv', format='csv', header=True)
Then convert this file into table using the code below:
%%pyspark
spark.sql("CREATE DATABASE IF NOT EXISTS business")
df.write.mode("overwrite").saveAsTable("business.data")
Refer below image.
Now you can run any Spark SQL command on this table as shown below:
%%pyspark
data = spark.sql("SELECT * FROM business.data")
display(data)
See the output in below image.

How to import MySQL metadata to Apache Atlas Without Storing Hive

How to import MySQL metadata to Apache Atlas using sqoop or Spark,
need to show actual RDBMS data types and its column in Apache Atlas
i tried MySQL to hive using sqoop
MySQL to Hive using Spark
I don't want to show Mysql to Hive, its only showing hive datatypes
is there any way to connect MySQL to Apache Atlas like JDBC connection, etc.

Is there a way to use Impala rather than Hive in PySpark?

I have queries that work in Impala but not Hive. I am creating a simply PySpark file such as:
from pyspark import SparkConf, SparkContext
from pyspark.sql import SQLContext, HiveContext
sconf = SparkConf()
sc = SparkContext.getOrCreate(conf=sconf)
sqlContext = HiveContext(sc)
sqlContext.sql('use db1')
...
When I run this script, it's queries get the errors I get when I run them in the Hive editor (they work in the Impala editor). Is there a way to fix this so that I can run these queries in the script using Impala?
You can use Impala or HiveServer2 in Spark SQL via JDBC Data Source. That requires you to install Impala JDBC driver, and configure connection to Impala in Spark application. But "you can" doesn't mean "you should", because it incurs overhead and creates extra dependencies without any particular benefits.
Typically (and that is what your current application is trying to do), Spark SQL runs against underlying file system directly, not needing to go through either HiveServer2 or Impala coordinators. In this scenario, Spark only (re)uses Hive Metastore to retrieve the metadata -- database and table definitions.

Running complex SQL queries on Cassandra tables using Spark SQL

hereI have setup Cassandra and Spark with cassandra- spark connector. I am able to create RDDs using Scala. But I would like to run complex SQL queries (Aggregation/Analytical functions/Window functions) using Spark SQL on Cassandra tables , could you help how should I proceed ?getting error like this
following is the query used :
sqlContext.sql(
"""CREATE TEMPORARY TABLE words
|USING org.apache.spark.sql.cassandra
|OPTIONS (
| table "words",
| keyspace "test",
| cluster "Test Cluster",
| pushdown "true"
|)""".stripMargin)
below is the error :[enter image description here][2]
new error:
enter image description here
First thing I noticed from your post is that , sqlContext.sql(...) used in your query but your screenshot shows sc.sql(...).
I take screenshot content as your actual issue. In Spark shell, Once you've loaded the shell, both the SparkContext (sc) and the SQLContext (sqlContext) are already loaded and ready to go. sql(...) does't exit in SparkContext so you should try with sqlContext.sql(...).
Most probably in your spark-shell context started as Spark Session and value for that is spark. Try your commands with spark instead of sqlContext.

Spark SQL build for hive?

I have downloaded spark release - 1.3.1 and package type is Pre-build for Hadoop 2.6 and later
now i want to run below scala code using spark shell so i followed this steps
1. bin/spark-shell
2. val sqlContext = new org.apache.spark.sql.hive.HiveContext(sc)
3. sqlContext.sql("CREATE TABLE IF NOT EXISTS src (key INT, value STRING)")
Now the problem is if i verity it on hue browser like
select * from src;
then i get
table not found exception
that means table not created how do i configure hive with spark shell to make this successful. i want to use SparkSQL also i need to read and write data from hive.
i randomly heard that we need to copy hive-site.xml file somewhere in spark directory
can someone please explain me with the steps - SparkSQL and Hive configuration
Thanks
Tushar
Indeed, the hive-site.xml direction is correct. Take a look at https://spark.apache.org/docs/latest/sql-programming-guide.html#hive-tables .
Also it sounds like you wish to create a hive table from spark, for that look at "Saving to Persistent Tables" in the same document as above.