Solr uses code from the Apache Tika project to provide a framework for incorporating many different file-format parsers such as Apache PDFBox and Apache POI into Solr itself. Working with this framework, Solr's
ExtractingRequestHandler can use Tika to support uploading binary files, including files in popular formats such as Word and PDF, for data extraction and indexing.
When this framework was under development, it was called the Solr Content Extraction Library or CEL; from that abbreviation came this framework's name: Solr Cell.
If you want to supply your own
ContentHandler for Solr to use, you can extend the
ExtractingRequestHandler and override the
createFactory() method. This factory is responsible for constructing the
literalsOverride, which normally defaults to *true, to *false" to append Tika-parsed values to literal values.
For more information on Solr's Extracting Request Handler, see https://wiki.apache.org/solr/ExtractingRequestHandler.
When using the Solr Cell framework, it is helpful to keep the following in mind:
- Tika will automatically attempt to determine the input document type (Word, PDF, HTML) and extract the content appropriately. If you like, you can explicitly specify a MIME type for Tika with the
- Tika works by producing an XHTML stream that it feeds to a SAX ContentHandler. SAX is a common interface implemented for many different XML parsers. For more information, see http://www.saxproject.org/quickstart.html.
- Solr then responds to Tika's SAX events and creates the fields to index.
- Tika produces metadata such as Title, Subject, and Author according to specifications such as the DublinCore. See http://tika.apache.org/1.7/formats.html for the file types supported.
- Tika adds all the extracted text to the
- You can map Tika's metadata fields to Solr fields. You can also boost these fields.
- You can pass in literals for field values. Literals will override Tika-parsed values, including fields in the Tika metadata object, the Tika content field, and any "captured content" fields.
- You can apply an XPath expression to the Tika XHTML to restrict the content that is produced.
While Apache Tika is quite powerful, it is not perfect and fails on some files. PDF files are particularly problematic, mostly due to the PDF format itself. In case of a failure processing any file, the
ExtractingRequestHandler does not have a secondary mechanism to try to extract some text from the file; it will throw an exception and fail.
Trying out Tika with the Solr
You can try out the Tika framework using the
techproducts example included in Solr.
Start the example:
You can now use curl to send a sample PDF file via HTTP POST:
The URL above calls the Extracting Request Handler, uploads the file
solr-word.pdf and assigns it the unique ID
doc1. Here's a closer look at the components of this command:
literal.id=doc1parameter provides the necessary unique ID for the document being indexed.
commit=true parametercauses Solr to perform a commit after indexing the document, making it immediately searchable. For optimum performance when loading many documents, don't call the commit command until you are done.
-Fflag instructs curl to POST data using the Content-Type
multipart/form-dataand supports the uploading of binary files. The @ symbol instructs curl to upload the attached file.
- The argument
firstname.lastname@example.org a valid path, which can be absolute or relative.
You can also use
bin/post to send a PDF file into Solr (without the params, the literal.id parameter would be set to the absolute path to the file):
Now you should be able to execute a query and find that document. You can make a request like
You may notice that although the content of the sample document has been indexed and stored, there are not a lot of metadata fields associated with this document. This is because unknown fields are ignored according to the default parameters configured for the
/update/extract handler in
solrconfig.xml, and this behavior can be easily changed or overridden. For example, to store and see all metadata and content, execute the following:
In this command, the
uprefix=attr_ parameter causes all generated fields that aren't defined in the schema to be prefixed with
attr_, which is a dynamic field that is stored and indexed.
This command allows you to query the document using an attribute, as in:
The table below describes the parameters accepted by the Extracting Request Handler.
Boosts the specified field by the defined float amount. (Boosting a field alters its importance in a query response. To learn about boosting fields, see Searching.)
Captures XHTML elements with the specified name for a supplementary addition to the Solr document. This parameter can be useful for copying chunks of the XHTML into a separate field. For instance, it could be used to grab paragraphs (
Indexes attributes of the Tika XHTML elements into separate fields, named after the element. If set to true, for example, when extracting from HTML, Tika can return the href attributes in <a> tags as fields named "a". See the examples below.
Add the document within the specified number of milliseconds.
Defines the date format patterns to identify in the documents.
If the uprefix parameter (see below) is not specified and a field cannot be determined, the default field will be used.
Default is false. If true, returns the extracted content from Tika without indexing the document. This literally includes the extracted XHTML as a string in the response. When viewing manually, it may be useful to use a response format other than XML to aid in viewing the embedded XHTML tags.For an example, see http://wiki.apache.org/solr/TikaExtractOnlyExampleOutput.
Default is "xml", but the other option is "text". Controls the serialization format of the extract content. The xml format is actually XHTML, the same format that results from passing the
Maps (moves) one field name to another. The
|ignoreTikaException||If true, exceptions found during processing will be skipped. Any metadata available, however, will be indexed.|
Populates a field with the name supplied with the specified value for each document. The data can be multivalued if the field is multivalued.
If true (the default), literal field values will override other values with the same field name. If false, literal values defined with
Values are "true" or "false". If true, all field names will be mapped to lowercase with underscores, if needed. For example, "Content-Type" would be mapped to "content_type."
Useful if uploading very large documents, this defines the KB size of documents to allow.
Defines a file path and name for a file of file name to password mappings.
Specifies the optional name of the file. Tika can use it as a hint for detecting a file's MIME type.
Defines a password to use for a password-protected PDF or OOXML file
Defines a file path and name to a customized Tika configuration file. This is only required if you have customized your Tika implementation.
Prefixes all fields that are not defined in the schema with the given prefix. This is very useful when combined with dynamic field definitions. Example:
When extracting, only return Tika XHTML content that satisfies the given XPath expression. See http://tika.apache.org/1.7/index.html for details on the format of Tika XHTML. See also http://wiki.apache.org/solr/TikaExtractOnlyExampleOutput.
Order of Operations
Here is the order in which the Solr Cell framework, using the Extracting Request Handler and Tika, processes its input.
- Tika generates fields or passes them in as literals specified by
literalsOverride=false, literals will be appended as multi-value to the Tika-generated field.
lowernames=true, Tika maps fields to lowercase.
- Tika applies the mapping rules specified by
uprefixis specified, any unknown field names are prefixed with that value, else if
defaultFieldis specified, any unknown fields are copied to the default field.
Configuring the Solr
If you are not working with the supplied
data_driven_schema_configs config set, you must configure your own
solrconfig.xml to know about the Jar's containing the
ExtractingRequestHandler and its dependencies:
You can then configure the
In the defaults section, we are mapping Tika's Last-Modified Metadata attribute to a field named
last_modified. We are also telling it to ignore undeclared fields. These are all overridden parameters.
tika.config entry points to a file containing a Tika configuration. The
date.formats allows you to specify various
java.text.SimpleDateFormats date formats for working with transforming extracted input to a Date. Solr comes configured with the following date formats (see the
DateUtil in Solr):
EEE MMM d hh:mm:ss z yyyy
EEE, dd MMM yyyy HH:mm:ss zzz
EEEE, dd-MMM-yy HH:mm:ss zzz
EEE MMM d HH:mm:ss yyyy
You may also need to adjust the
multipartUploadLimitInKB attribute as follows if you are submitting very large documents.
Parser specific properties
Parsers used by Tika may have specific properties to govern how data is extracted. For instance, when using the Tika library from a Java program, the PDFParserConfig class has a method setSortByPosition(boolean) that can extract vertically oriented text. To access that method via configuration with the ExtractingRequestHandler, one can add the parseContext.config property to the solrconfig.xml file (see above) and then set properties in Tika's PDFParserConfig as below. Consult the Tika Java API documentation for configuration parameters that can be set for any particular parsers that require this level of control.
For a multi-core configuration, you can specify
sharedLib='lib' in the
<solr/> section of
solr.xml and place the necessary jar files there.
For more information about Solr cores, see The Well-Configured Solr Instance.
Indexing Encrypted Documents with the ExtractingUpdateRequestHandler
The ExtractingRequestHandler will decrypt encrypted files and index their content if you supply a password in either
resource.password on the request, or in a
In the case of
passwordsFile, the file supplied must be formatted so there is one line per rule. Each rule contains a file name regular expression, followed by "=", then the password in clear-text. Because the passwords are in clear-text, the file should have strict access restrictions.
As mentioned before, Tika produces metadata about the document. Metadata describes different aspects of a document, such as the author's name, the number of pages, the file size, and so on. The metadata produced depends on the type of document submitted. For instance, PDFs have different metadata than Word documents do.
In addition to Tika's metadata, Solr adds the following metadata (defined in
The name of the Content Stream as uploaded to Solr. Depending on how the file is uploaded, this may or may not be set
Any source info about the stream. (See the section on Content Streams later in this section.)
The size of the stream in bytes.
The content type of the stream, if available.
We recommend that you try using the
extractOnly option to discover which values Solr is setting for these metadata elements.
Examples of Uploads Using the Extracting Request Handler
Capture and Mapping
The command below captures
<div> tags separately, and then maps all the instances of that field to a dynamic field named
Capture, Mapping, and Boosting
The command below captures
<div> tags separately, maps the field to a dynamic field named
foo_t, then boosts
foo_t by 3.
Using Literals to Define Your Own Metadata
To add in your own metadata, pass in the literal parameter along with the file:
The example below passes in an XPath expression to restrict the XHTML returned by Tika:
Extracting Data without Indexing It
Solr allows you to extract data without indexing. You might want to do this if you're using Solr solely as an extraction server or if you're interested in testing Solr extraction.
The example below sets the
extractOnly=true parameter to extract data without indexing it.
The output includes XML generated by Tika (and further escaped by Solr's XML) using a different output format to make it more readable (`-out yes` instructs the tool to echo Solr's output to the console):
Sending Documents to Solr with a POST
The example below streams the file as the body of the POST, which does not, then, provide information to Solr about the name of the file.
Sending Documents to Solr with Solr Cell and SolrJ
SolrJ is a Java client that you can use to add documents to the index, update the index, or query the index. You'll find more information on SolrJ in Client APIs.
Here's an example of using Solr Cell and SolrJ to add documents to a Solr index.
First, let's use SolrJ to create a new SolrClient, then we'll construct a request containing a ContentStream (essentially a wrapper around a file) and sent it to Solr:
This operation streams the file
my-file.pdf into the Solr index for
The sample code above calls the extract command, but you can easily substitute other commands that are supported by Solr Cell. The key class to use is the
ContentStreamUpdateRequest, which makes sure the ContentStreams are set properly. SolrJ takes care of the rest.
Note that the
ContentStreamUpdateRequest is not just specific to Solr Cell. You can send CSV to the CSV Update handler and to any other Request Handler that works with Content Streams for updates.
|Uploading Data with Index Handlers||Indexing and Basic Data Operations||Uploading Structured Data Store Data with the Data Import Handler|