Importing a text file into a table
This example shows how to use Spark to import a local or DSEFS based text file into an existing table.
This example shows how to use Spark to import a local or DSEFS based text file into
an existing table. You use the saveToCassandra
method present in
the Spark RDDs to save an arbitrary RDD to the database.
Procedure
-
Create a keyspace and a table in the database. For example, use
cqlsh
.CREATE KEYSPACE int_ks WITH replication = {'class': 'NetworkTopologyStrategy', 'Analytics':1}; USE int_ks; CREATE TABLE int_compound ( pkey int, ckey1 int, data1 int , PRIMARY KEY (pkey,ckey1));
-
Insert data into the table
INSERT INTO int_compound ( pkey, ckey1, data1 ) VALUES ( 1, 2, 3 ); INSERT INTO int_compound ( pkey, ckey1, data1 ) VALUES ( 2, 3, 4 ); INSERT INTO int_compound ( pkey, ckey1, data1 ) VALUES ( 3, 4, 5 ); INSERT INTO int_compound ( pkey, ckey1, data1 ) VALUES ( 4, 5, 1 ); INSERT INTO int_compound ( pkey, ckey1, data1 ) VALUES ( 5, 1, 2 );
-
Create a text file named normalfill.csv that contains this
data.
6,7,8 7,8,6 8,6,7
-
Put the CSV file into DSEFS. For example:
dse fs "put file://mypath/normalfill.csv dsefs:/"
- Start the Spark shell.
-
Verify that Spark can access the
int_ks
keyspace::showSchema int_ks
======================================== Keyspace: int_ks ======================================== Table: int_compound ---------------------------------------- - pkey : Int (partition key column) - ckey1 : Int (clustering column) - data1 : Int
int_ks
appears in the list of keyspaces. -
Read in the file, splitting it on the comma delimiter. Transform each element
into an Integer.
val normalfill = sc.textFile("/normalfill.csv").map(line => line.split(",").map(_.toInt));
normalfill: org.apache.spark.rdd.RDD[Array[Int]] = MappedRDD[2] at map at console:22
Alternatively, read in the file from the local file system.val file = sc.textFile("file:///local-path/normalfill.csv")
file: org.apache.spark.rdd.RDD[String] = MappedRDD[4] at textFile at console:22
-
Check that Spark can find and read the CSV file.
normalfill.take(1);
res2: Array[Array[Int]] = Array(Array(6, 7, 8))
-
Save the new data to the database.
normalfill.map(line => (line(0), line(1), line(2))).saveToCassandra( "int_ks", "int_compound", Seq("pkey", "ckey1", "data1"))
The step produces no output. -
Check that the data was saved using
cqlsh
.SELECT * FROM int_ks.int_compound;
pkey | ckey1 | data1 ------+-------+------- 5 | 1 | 2 1 | 2 | 3 8 | 6 | 7 2 | 3 | 4 4 | 5 | 1 7 | 8 | 6 6 | 7 | 8 3 | 4 | 5 (8 rows)