Abstract: In some examples, a system performs a delimiter identification process that includes identifying candidate record delimiters and candidate field delimiters in the input data, and providing different pairs of candidate record delimiters and candidate field delimiters. For each respective pair of the different pairs, the system identifies records using the corresponding candidate record delimiter of the respective pair, and computes a collection of measures including a measure indicating a quantity of unique fields observed in the records identified using the corresponding field delimiter of the respective pair. The system selects, based on values of the collection of measures computed for corresponding pairs of the different pairs, a record delimiter and a field delimiter in a pair of the different pairs.

Abstract: In some examples, a system performs a delimiter identification process that includes identifying candidate record delimiters and candidate field delimiters in the input data, and providing different pairs of candidate record delimiters and candidate field delimiters. For each respective pair of the different pairs, the system identifies records using the corresponding candidate record delimiter of the respective pair, and computes a collection of measures including a measure indicating a quantity of unique fields observed in the records identified using the corresponding field delimiter of the respective pair. The system selects, based on values of the collection of measures computed for corresponding pairs of the different pairs, a record delimiter and a field delimiter in a pair of the different pairs.

Abstract: A multi-parameter data type framework can, among other things, provide a more comprehensive, systematic, and/or formal mechanisms for determining an appropriate data type for a data set. For example, the multi-parameter data type framework can be used to allow analytic tools to virtually automatically figure out an appropriate data type for a set of data values.