Abstract: A method for creating a semantically aggregated index in an indexer-agnostic index building system includes: extracting documents from a data source, each document including a data object; distributing the documents to a plurality of processing nodes within the system; for each node: indexing the data objects for each document into fields using semantic rules; and grouping indexed data objects for related fields by: classifying the documents into logical groups based on the semantic rules; and creating a searchable index shard for related logical groups.

Abstract: A computer program product for an indexer-agnostic index building system includes a computer readable storage medium to store a computer readable program, wherein the computer readable program, when executed on a computer, causes the computer to perform operations for creating a semantically aggregated index. The operations include: extracting documents from a data source, wherein each document includes a data object; distributing the documents to a plurality of processing nodes within the system; for each node: indexing the data objects for each document into fields using semantic rules; and grouping indexed data objects for related fields by: classifying the documents into logical groups based on the semantic rules; and creating a searchable index shard for related logical groups.

Abstract: Embodiments of the invention relate to building a distributed reverse semantic index. In one general embodiment a plurality of documents are received with each document having at least one defined rule and or semantic. The documents are distributed among a plurality of nodes of a system. The documents are processed in a generally parallel fashion. Processing the documents includes processing text data of each of the document and breaking each document into fields to index the text data to create index data by deferring how to categorize the text data based upon the defined rule and or semantics. The indexed data is combined back together to create an indexer-agnostic semantic index including a plurality of the semantic index shards and to semantically classify the documents based on the index shards into groups based on document type to create the distributed reverse semantic index.

Abstract: A method for creating a semantically aggregated index in an indexer-agnostic index building system includes: extracting documents from a data source, each document including a data object; distributing the documents to a plurality of processing nodes within the system; for each node: indexing the data objects for each document into fields using semantic rules; and grouping indexed data objects for related fields by: classifying the documents into logical groups based on the semantic rules; and creating a searchable index shard for related logical groups.

Abstract: Embodiments of the invention relate to building a distributed reverse semantic index. In one general embodiment a plurality of documents are received with each document having at least one defined rule and or semantic. The documents are distributed among a plurality of nodes of a system. The documents are processed in a generally parallel fashion. Processing the documents includes processing text data of each of the document and breaking each document into fields to index the text data to create index data by deferring how to categorize the text data based upon the defined rule and or semantics. The indexed data is combined back together to create an indexer-agnostic semantic index including a plurality of the semantic index shards and to semantically classify the documents based on the index shards into groups based on document type to create the distributed reverse semantic index.

Abstract: A computer program product for an indexer-agnostic index building system includes a computer readable storage medium to store a computer readable program, wherein the computer readable program, when executed on a computer, causes the computer to perform operations for creating a semantically aggregated index. The operations include: extracting documents from a data source, wherein each document includes a data object; distributing the documents to a plurality of processing nodes within the system; for each node: indexing the data objects for each document into fields using semantic rules; and grouping indexed data objects for related fields by: classifying the documents into logical groups based on the semantic rules; and creating a searchable index shard for related logical groups.