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https://issues.apache.org/jira/browse/SPARK-11190?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14968031#comment-14968031
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Shivaram Venkataraman commented on SPARK-11190:
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We do convert maps in Scala to environments in R when we convert the data. Is
there a problem with the conversion ?
> SparkR support for cassandra collection types.
> -----------------------------------------------
>
> Key: SPARK-11190
> URL: https://issues.apache.org/jira/browse/SPARK-11190
> Project: Spark
> Issue Type: Bug
> Components: SparkR
> Affects Versions: 1.5.1
> Environment: SparkR Version: 1.5.1
> Cassandra Version: 2.1.6
> R Version: 3.2.2
> Cassandra Connector version: 1.5.0-M2
> Reporter: Bilind Hajer
> Labels: cassandra, dataframe, sparkR
>
> I want to create a data frame from a Cassandra keyspace and column family in
> sparkR.
> I am able to create data frames from tables which do not include any
> Cassandra collection datatypes,
> such as Map, Set and List. But, many of the schemas that I need data from,
> do include these collection data types.
> Here is my local environment.
> SparkR Version: 1.5.1
> Cassandra Version: 2.1.6
> R Version: 3.2.2
> Cassandra Connector version: 1.5.0-M2
> To test this issue, I did the following iterative process.
> sudo ./sparkR --packages
> com.datastax.spark:spark-cassandra-connector_2.10:1.5.0-M2 --conf
> spark.cassandra.connection.host=127.0.0.1
> Running this command, with sparkR gives me access to the spark cassandra
> connector package I need,
> and connects me to my local cqlsh server ( which is up and running while
> running this code in sparkR shell ).
> CREATE TABLE test_table (
> column_1 int,
> column_2 text,
> column_3 float,
> column_4 uuid,
> column_5 timestamp,
> column_6 boolean,
> column_7 timeuuid,
> column_8 bigint,
> column_9 blob,
> column_10 ascii,
> column_11 decimal,
> column_12 double,
> column_13 inet,
> column_14 varchar,
> column_15 varint,
> PRIMARY KEY( ( column_1, column_2 ) )
> );
> All of the above data types are supported. I insert dummy data after creating
> this test schema.
> For example, now in my sparkR shell, I run the following code.
> df.test <- read.df(sqlContext, source = "org.apache.spark.sql.cassandra",
> keyspace = "datahub", table = "test_table")
> assigns with no errors, then,
> > schema(df.test)
> StructType
> |-name = "column_1", type = "IntegerType", nullable = TRUE
> |-name = "column_2", type = "StringType", nullable = TRUE
> |-name = "column_10", type = "StringType", nullable = TRUE
> |-name = "column_11", type = "DecimalType(38,18)", nullable = TRUE
> |-name = "column_12", type = "DoubleType", nullable = TRUE
> |-name = "column_13", type = "InetAddressType", nullable = TRUE
> |-name = "column_14", type = "StringType", nullable = TRUE
> |-name = "column_15", type = "DecimalType(38,0)", nullable = TRUE
> |-name = "column_3", type = "FloatType", nullable = TRUE
> |-name = "column_4", type = "UUIDType", nullable = TRUE
> |-name = "column_5", type = "TimestampType", nullable = TRUE
> |-name = "column_6", type = "BooleanType", nullable = TRUE
> |-name = "column_7", type = "UUIDType", nullable = TRUE
> |-name = "column_8", type = "LongType", nullable = TRUE
> |-name = "column_9", type = "BinaryType", nullable = TRUE
> Schema is correct.
> > class(df.test)
> [1] "DataFrame"
> attr(,"package")
> [1] "SparkR"
> df.test is clearly defined to be a DataFrame Object.
> > head(df.test)
> column_1 column_2 column_10 column_11 column_12 column_13 column_14
> column_15
> 1 1 hello NA NA NA NA NA
> NA
> column_3 column_4 column_5 column_6 column_7 column_8 column_9
> 1 3.4 NA NA NA NA NA NA
> sparkR is reading from the column_family correctly, but now lets add a
> collection data type to the schema.
> Now I will drop that test_table, and recreate the table, with with an extra
> column of data type map<text,int>
> CREATE TABLE test_table (
> column_1 int,
> column_2 text,
> column_3 float,
> column_4 uuid,
> column_5 timestamp,
> column_6 boolean,
> column_7 timeuuid,
> column_8 bigint,
> column_9 blob,
> column_10 ascii,
> column_11 decimal,
> column_12 double,
> column_13 inet,
> column_14 varchar,
> column_15 varint,
> column_16 map<text,int>,
> PRIMARY KEY( ( column_1, column_2 ) )
> );
> After inserting dummy data into the new test schema,
> > df.test <- read.df(sqlContext, source = "org.apache.spark.sql.cassandra",
> > keyspace = "datahub", table = "test_table")
> assigns with no errors,
> > schema(df.test)
> StructType
> |-name = "column_1", type = "IntegerType", nullable = TRUE
> |-name = "column_2", type = "StringType", nullable = TRUE
> |-name = "column_10", type = "StringType", nullable = TRUE
> |-name = "column_11", type = "DecimalType(38,18)", nullable = TRUE
> |-name = "column_12", type = "DoubleType", nullable = TRUE
> |-name = "column_13", type = "InetAddressType", nullable = TRUE
> |-name = "column_14", type = "StringType", nullable = TRUE
> |-name = "column_15", type = "DecimalType(38,0)", nullable = TRUE
> |-name = "column_16", type = "MapType(StringType,IntegerType,true)", nullable
> = TRUE
> |-name = "column_3", type = "FloatType", nullable = TRUE
> |-name = "column_4", type = "UUIDType", nullable = TRUE
> |-name = "column_5", type = "TimestampType", nullable = TRUE
> |-name = "column_6", type = "BooleanType", nullable = TRUE
> |-name = "column_7", type = "UUIDType", nullable = TRUE
> |-name = "column_8", type = "LongType", nullable = TRUE
> |-name = "column_9", type = "BinaryType", nullable = TRUE
> correct schema is returned.
> > class(df.test)
> [1] "DataFrame"
> attr(,"package")
> [1] "SparkR"
> Object is a DataFrame, but now when we see if the dataFrame actually contains
> records from the column_family.
> > head(df.test)
> Error in as.data.frame.default(x[[i]], optional = TRUE) :
> cannot coerce class ""jobj"" to a data.frame
> Note, I will always get the above error, when calling head on a data frame
> that is read from a cassandra column_family
> that has one or more cassandra collection data types (list, set, map).
> I know R has list and vector data types which can probably be used to support
> Cassandra Sets, and Lists, but for Map,
> there are packages which enable Hash support, which can be used to replicate
> a cassandra map data type.
> Could we log this as a bug? Cassandra collection data types are widely used
> in our schemas,
> and we want to be able to build data frame from those Cassandra schemas.
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