2. Zebra Features Overview

2.1. Zebra Document Model

Table 1.1. Zebra document model

Complex semi-structured DocumentsXML and GRS-1 DocumentsBoth XML and GRS-1 documents exhibit a DOM like internal representation allowing for complex indexing and display rulesChapter 8, ALVIS XML Record Model and Filter Module and Chapter 9, GRS-1 Record Model and Filter Modules
Input document formatsXML, SGML, Text, ISO2709 (MARC) A system of input filters driven by regular expressions allows most ASCII-based data formats to be easily processed. SGML, XML, ISO2709 (MARC), and raw text are also supported.Section 2.5, “Record Models and Filter Modules”
Document storageIndex-only, Key storage, Document storageData can be, and usually is, imported into Zebra's own storage, but Zebra can also refer to external files, building and maintaining indexes of "live" collections. 

2.2. Zebra Search Features

Table 1.2. Zebra search functionality

Query languagesCQL and RPN/PQFThe type-1 Reverse Polish Notation (RPN) and its textual representation Prefix Query Format (PQF) are supported. The Common Query Language (CQL) can be configured as a mapping from CQL to RPN/PQFSection 1.1.1, “Prefix Query Format (PQF)” and Section 4, “Server Side CQL to PQF Query Translation”
Complex boolean query treeCQL and RPN/PQFBoth CQL and RPN/PQF allow atomic query parts (APT) to be combined into complex boolean query treesSection 2.1, “RPN tree structure”
Field searchuser definedAtomic query parts (APT) are either general, or directed at user-specified document fields Section 2.1.3, “Atomic queries (APT)”, Section 2.1.5, “Zebra's special access point of type 'string'”, Section 2.3.1, “Use Attributes (type 1)”, and Section 3.4.1, “IDXPATH Use Attributes (type = 1)”
Data normalizationuser definedData normalization, text tokenization and character mappings can be applied during indexing and searchingChapter 10, Field Structure and Character Sets
Predefined field typesuser definedData fields can be indexed as phrase, as into word tokenized text, as numeric values, URLs, dates, and raw binary data.Section 2, “Charmap Files” and Section 3.5.2, “Mapping of PQF APT structure and completeness to register type”
Regular expression matchingavailableFull regular expression matching and "approximate matching" (e.g. spelling mistake corrections) are handled.Section 3.6, “Zebra Regular Expressions in Truncation Attribute (type = 5)”
Term truncationleft, right, left-and-rightThe truncation attribute specifies whether variations of one or more characters are allowed between search term and hit terms, or not. Using non-default truncation attributes will broaden the document hit set of a search query.Section 2.4.4, “Truncation Attributes (type = 5)”
Fuzzy searchesSpelling correctionIn addition, fuzzy searches are implemented, where one spelling mistake in search terms is matchedSection 2.4.4, “Truncation Attributes (type = 5)”

2.3. Zebra Index Scanning

Table 1.3. Zebra index scanning

Scanterm suggestionsScan on a given named index returns all the indexed terms in lexicographical order near the given start term. This can be used to create drop-down menus and search suggestions.Section 1.2.3, “Scan Operation” and Section 2.1.3, “Atomic queries (APT)”
Facetted browsingavailableZebra 2.1 and allows retrieval of facets for a result set. Section 3.3, “Zebra specific Scan Extensions to all Attribute Sets”
Drill-down or refine-searchpartiallyscanning in result sets can be used to implement drill-down in search clientsSection 3.3, “Zebra specific Scan Extensions to all Attribute Sets”

2.4. Zebra Document Presentation

Table 1.4. Zebra document presentation

Hit countyesSearch results include at any time the total hit count of a given query, either exact computed, or approximative, in case that the hit count exceeds a possible pre-defined hit set truncation level. Section 3.2.4, “Local Approximative Limit Attribute (type 11)” and Section 2, “The Zebra Configuration File”
Paged result setsyesPaging of search requests and present/display request can return any successive number of records from any start position in the hit set, i.e. it is trivial to provide search results in successive pages of any size. 
XML document transformationsXSLT based Record presentation can be performed in many pre-defined XML data formats, where the original XML records are on-the-fly transformed through any preconfigured XSLT transformation. It is therefore trivial to present records in short/full XML views, transforming to RSS, Dublin Core, or other XML based data formats, or transform records to XHTML snippets ready for inserting in XHTML pages. Section 2.2, “ALVIS Exchange Formats”
Binary record transformationsMARC, USMARC, MARC21 and MARCXMLpost-filter record transformations 
Record Syntaxes  Multiple record syntaxes for data retrieval: GRS-1, SUTRS, XML, ISO2709 (MARC), etc. Records can be mapped between record syntaxes and schemas on the fly. 
Zebra internal metadatayes Zebra internal document metadata can be fetched in SUTRS and XML record syntaxes. Those are useful in client applications.Section 4, “Retrieval of Zebra internal record data”
Zebra internal raw record datayes Zebra internal raw, binary record data can be fetched in SUTRS and XML record syntaxes, leveraging %zebra; to a binary storage systemSection 4, “Retrieval of Zebra internal record data”
Zebra internal record field datayes Zebra internal record field data can be fetched in SUTRS and XML record syntaxes. This makes very fast minimal record data displays possible.Section 4, “Retrieval of Zebra internal record data”

2.5. Zebra Sorting and Ranking

Table 1.5. Zebra sorting and ranking

Sortnumeric, lexicographicSorting on the basis of alpha-numeric and numeric data is supported. Alphanumeric sorts can be configured for different data encodings and locales for European languages.Section 9.4, “Sorting” and Section 3.2.1, “Zebra Extension Embedded Sort Attribute (type 7)”
Combined sortingyesSorting on the basis of combined sorts ­ e.g. combinations of ascending/descending sorts of lexicographical/numeric/date field data is supportedSection 9.4, “Sorting”
Relevance rankingTF-IDF likeRelevance-ranking of free-text queries is supported using a TF-IDF like algorithm.Section 9.3, “Dynamic Ranking”
Static pre-rankingyesEnables pre-index time ranking of documents where hit lists are ordered first by ascending static rank, then by ascending document ID.Section 9.2, “Static Ranking”

2.6. Zebra Live Updates

Table 1.6. Zebra live updates

Incremental and batch updates It is possible to schedule record inserts/updates/deletes in any quantity, from single individual handled records to batch updates in strikes of any size, as well as total re-indexing of all records from file system. zebraidx(1)
Remote updatesZ39.50 extended servicesUpdates can be performed from remote locations using the Z39.50 extended services. Access to extended services can be login-password protected.Section 10, “Extended Services: Remote Insert, Update and Delete” and Section 2, “The Zebra Configuration File”
Live updatestransaction based Data updates are transaction based and can be performed on running Zebra systems. Full searchability is preserved during life data update due to use of shadow disk areas for update operations. Multiple update transactions at the same time are lined up, to be performed one after each other. Data integrity is preserved.Section 8, “Safe Updating - Using Shadow Registers”

2.7. Zebra Networked Protocols

Table 1.7. Zebra networked protocols

Fundamental operationsZ39.50/SRU explain, search, scan, and update Section 1.2, “Operation types”
Z39.50 protocol supportyes Protocol facilities supported are: init, search, present (retrieval), Segmentation (support for very large records), delete, scan (index browsing), sort, close and support for the update Extended Service to add or replace an existing XML record. Piggy-backed presents are honored in the search request. Named result sets are supported.the section called “Z39.50 Protocol Support and Behavior”
Web Service supportSRU The protocol operations explain, searchRetrieve and scan are supported. CQL to internal query model RPN conversion is supported. Extended RPN queries for search/retrieve and scan are supported.the section called “SRU Protocol Support and Behavior”

2.8. Zebra Data Size and Scalability

Table 1.8. Zebra data size and scalability

No of records40-60 million  
Data size100 GB of record dataZebra based applications have successfully indexed up to 100 GB of record data 
Scale outmultiple discs  
PerformanceO(n * log N) Zebra query speed and performance is affected roughly by O(log N), where N is the total database size, and by O(n), where n is the specific query hit set size. 
Average search times  Even on very large size databases hit rates of 20 queries per seconds with average query answering time of 1 second are possible, provided that the boolean queries are constructed sufficiently precise to result in hit sets of the order of 1000 to 5.000 documents. 
Large databases64 bit file pointers64 file pointers assure that register files can extend the 2 GB limit. Logical files can be automatically partitioned over multiple disks, thus allowing for large databases. 

2.9. Zebra Supported Platforms

Table 1.9. Zebra supported platforms

Linux GNU Linux (32 and 64bit), journaling Reiser or (better) JFS file system on disks. NFS file systems are not supported. GNU/Debian Linux packages are availableSection 2, “GNU/Debian”
Unixtar-ballZebra is written in portable C, so it runs on most Unix-like systems. Usual tar-ball install possible on many major Unix systemsSection 1, “UNIX”
WindowsNT/2000/2003/XPZebra runs as well on Windows (NT/2000/2003/XP). Windows installer packages availableSection 3, “Windows”