SPARKC-706: Add basic support for Cassandra vectors #1366
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Great work! :)
Please have a look at the minor comments and add a note with a large font in the main README stating that the vector type is now supported. Additionally, please add a document showcasing how it can be used (examples taken from tests should be okay here).
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| /** Skips the given test if the Cluster Version is lower or equal to the given version */ | ||
| def from(version: Version)(f: => Unit): Unit = { | ||
| private def from(version: Version)(f: => Unit): Unit = { |
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This doc is not correct, right? It skips only when the version is lower.
| @@ -147,16 +147,24 @@ trait SparkCassandraITSpecBase | |||
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| /** Skips the given test if the Cluster Version is lower or equal to the given `cassandra` Version or `dse` Version | |||
| * (if this is a DSE cluster) */ | |||
| def from(cassandra: Version, dse: Version)(f: => Unit): Unit = { | |||
| def from(cassandra: Version, dse: Version)(f: => Unit): Unit = from(Some(cassandra), Some(dse))(f) | |||
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use Option instead of Some
| CaseClassType <: Product : ClassTag : TypeTag : ColumnMapper: RowReaderFactory : ValidRDDType](typeName: String) extends SparkCassandraITFlatSpecBase with DefaultCluster | ||
| { | ||
| /** Skips the given test if the cluster is not Cassandra */ | ||
| override def cassandraOnly(f: => Unit): Unit = super.cassandraOnly(f) |
| def createVectorTable(session: CqlSession, table: String): Unit = { | ||
| session.execute( | ||
| s"""CREATE TABLE IF NOT EXISTS $ks.$table ( | ||
| | id INT PRIMARY KEY, |
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Can a vector be a primary key?
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Perhaps, why do you ask?
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Wondering if that's supported.
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| private def hasVectors(rows: List[Row], expectedVectors: Seq[Seq[ScalaType]]): Unit = { |
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Maybe assertVectors would be more clear as the method doesn't return boolean, instead it asserts on the content.
| implicitly[TypeTag[CqlVector[T]]] | ||
| } | ||
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| def newCollection(items: Iterable[Any]): java.util.List[T] = { |
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| def newCollection(items: Iterable[Any]): java.util.List[T] = { | ||
| val buf = new java.util.ArrayList[T](dimension) |
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Why java collection here?
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This collection is passed to CqlVector.getInstance which expects either Java List or array. If we use here a Scala collection and then let JavaConverters adjust that, we will have to create one extra wrapper which is a waste in this case.
| @@ -184,7 +184,49 @@ val street = address.getString("street") | |||
| val number = address.getInt("number") | |||
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| [//]: # (TODO loading vectors) | |||
| ### Reading vectors | |||
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Should we add similar docs to https://github.com/datastax/spark-cassandra-connector/blob/master/doc/14_data_frames.md ?
Description
How did the Spark Cassandra Connector Work or Not Work Before this Patch
Describe the problem, or state of the project that this patch fixes. Explain
why this is a problem if this isn't obvious.
Example:
"When I read from tables with 3 INTS I get a ThreeIntException(). This is a problem because I often want to read from a table with three integers."
General Design of the patch
How the fix is accomplished, were new parameters or classes added? Why did you
pursue this particular fix?
Example: "I removed the incorrect assertion which would throw the ThreeIntException. This exception was incorrectly added and the assertion is not actually needed."
Fixes: Put JIRA Reference HERE
How Has This Been Tested?
Almost all changes and especially bug fixes will require a test to be added to either the integration or Unit Tests. Any tests added will be automatically run on travis when the pull request is pushed to github. Be sure to run suites locally as well.
Checklist: