Known issues and limitations

The following limitations apply to Cloudera Streaming Analytics 1.4.

SQL Stream Builder

Big numbers are incorrectly represented on the Streaming SQL Console UI
The issue impacts the following scenarios in Streaming SQL Console:
  • When having integers bigger than 253-1 among your values, the Input transformations and User Defined Functions are considered unsafe and produce incorrect results as these numbers will lose precision during parsing.
  • When having integers bigger than 253-1 among your values, sampling to the Streaming SQL Console UI produces incorrect results as these numbers will lose precision during parsing.

Flink

In Cloudera Streaming Analytics, the following SQL API features are in preview:
  • Match recognize
  • Top-N
  • Stream-Table join (without rowtime input)
DataStream conversion limitations
  • Converting between Tables and POJO DataStreams is currently not supported in CSA.
  • Object arrays are not supported for Tuple conversion.
  • The java.time class conversions for Tuple DataStreams are only supported by using explicit TypeInformation: LegacyInstantTypeInfo, LocalTimeTypeInfo.getInfoFor(LocalDate/LocalDateTime/LocalTime.class).
  • Only java.sql.Timestamp is supported for rowtime conversion, java.time.LocalDateTime is not supported.
Kudu catalog limitations
  • CREATE TABLE
    • Primary keys can only be set by the kudu.primary-key-columns property. Using the PRIMARY KEY constraint is not yet possible.
    • Range partitioning is not supported.
  • When getting a table through the catalog, NOT NULL and PRIMARY KEY constraints are ignored. All columns are described as being nullable, and not being primary keys.
  • Kudu tables cannot be altered through the catalog other than simply renaming them.
Schema Registry catalog limitations
  • Currently, the Schema Registry catalog / format only supports reading messages with the latest enabled schema for any given Kafka topic at the time when the SQL query was compiled.
  • No time-column and watermark support for Registry tables.
  • No CREATE TABLE support. Schemas have to be registered directly in the SchemaRegistry to be accessible through the catalog.
  • The catalog is read-only. It does not support table deletions or modifications.
  • By default, it is assumed that Kafka message values contain the schema id as a prefix, because this is the default behaviour for the SchemaRegistry Kafka producer format. To consume messages with schema written in the header, the following property must be set for the Registry client: store.schema.version.id.in.header: true.