Blast

Blast is a full text search and indexing server written in Go built on top of Bleve.
It provides functions through gRPC (HTTP/2 + Protocol Buffers) or traditional RESTful API (HTTP/1.1 + JSON).
Blast implements Raft consensus algorithm by hashicorp/raft. It achieve consensus across all the instances of the nodes, ensuring that every change made to the system is made to a quorum of nodes, or none at all. Blast makes it easy for programmers to develop search applications with advanced features.

Features

  • Full-text search and indexing
  • Faceting
  • Result highlighting
  • Easy deployment
  • Bringing up cluster
  • Index replication
  • An easy-to-use HTTP API
  • CLI is also available
  • Docker container image is available

Installing dependencies

Blast requires some C/C++ libraries if you need to enable cld2, icu, libstemmer or leveldb. The following sections are instructions for satisfying dependencies on particular platforms.

Ubuntu 18.10

$ sudo apt-get install -y \
    libicu-dev \
    libstemmer-dev \
    libleveldb-dev \
    gcc-4.8 \
    g++-4.8 \
    build-essential

$ sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-8 80
$ sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-8 80
$ sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-4.8 90
$ sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-4.8 90

$ export GOPATH=${HOME}/go
$ go get -u -v github.com/blevesearch/cld2
$ cd ${GOPATH}/src/github.com/blevesearch/cld2
$ git clone https://github.com/CLD2Owners/cld2.git
$ cd cld2/internal
$ ./compile_libs.sh
$ sudo cp *.so /usr/local/lib

macOS High Sierra Version 10.13.6

$ brew install \
    icu4c \
    leveldb

$ export GOPATH=${HOME}/go
$ go get -u -v github.com/blevesearch/cld2
$ cd ${GOPATH}/src/github.com/blevesearch/cld2
$ git clone https://github.com/CLD2Owners/cld2.git
$ cd cld2/internal
$ perl -p -i -e 's/soname=/install_name,/' compile_libs.sh
$ ./compile_libs.sh
$ sudo cp *.so /usr/local/lib

Building Blast

When you satisfied dependencies, let's build Blast for Linux as following:

$ mkdir -p ${GOPATH}/src/github.com/mosuka
$ cd ${GOPATH}/src/github.com/mosuka
$ git clone https://github.com/mosuka/blast.git
$ cd blast
$ make build

If you want to build for other platform, set GOOS, GOARCH environment variables. For example, build for macOS like following:

$ make \
    GOOS=darwin \
    build

Blast supports some Bleve Extensions (blevex). If you want to build with them, please set CGO_LDFLAGS, CGO_CFLAGS, CGO_ENABLED and BUILD_TAGS. For example, build LevelDB to be available for index storage as follows:

$ make \
    GOOS=linux \
    BUILD_TAGS=leveldb \
    CGO_ENABLED=1 \
    build

You can enable all the Bleve extensions supported by Blast as follows:

Linux

$ make \
    GOOS=linux \
    BUILD_TAGS="kagome icu libstemmer cld2 cznicb leveldb badger" \
    CGO_ENABLED=1 \
    build

macOS

$ make \
    GOOS=darwin \
    BUILD_TAGS="kagome icu libstemmer cld2 cznicb leveldb badger" \
    CGO_ENABLED=1 \
    CGO_LDFLAGS="-L/usr/local/opt/icu4c/lib" \
    CGO_CFLAGS="-I/usr/local/opt/icu4c/include" \
    build

Build flags

Please refer to the following table for details of Bleve Extensions:

BUILD_TAGS CGO_ENABLED Description
cld2 1 Enable Compact Language Detector
kagome 0 Enable Japanese Language Analyser
icu 1 Enable ICU Tokenizer, Thai Language Analyser
libstemmer 1 Enable Language Stemmer (Danish, German, English, Spanish, Finnish, French, Hungarian, Italian, Dutch, Norwegian, Portuguese, Romanian, Russian, Swedish, Turkish)
cznicb 0 Enable cznicb KV store
leveldb 1 Enable LevelDB
badger 0 Enable Badger (This feature is considered experimental)

If you want to enable the feature whose CGO_ENABLE is 1, please install it referring to the Installing dependencies section above.

Binaries

You can see the binary file when build successful like so:

$ ls ./bin
blast-indexer

Testing Blast

If you want to test your changes, run command like following:

$ make \
    test

You can test with all the Bleve extensions supported by Blast as follows:

Linux

$ make \
    GOOS=linux \
    BUILD_TAGS="kagome icu libstemmer cld2 cznicb leveldb badger" \
    CGO_ENABLED=1 \
    test

macOS

$ make \
    GOOS=darwin \
    BUILD_TAGS="kagome icu libstemmer cld2 cznicb leveldb badger" \
    CGO_ENABLED=1 \
    CGO_LDFLAGS="-L/usr/local/opt/icu4c/lib" \
    CGO_CFLAGS="-I/usr/local/opt/icu4c/include" \
    test

Packaging Blast

Linux

$ make \
    GOOS=linux \
    BUILD_TAGS="kagome icu libstemmer cld2 cznicb leveldb badger" \
    CGO_ENABLED=1 \
    dist

macOS

$ make \
    GOOS=darwin \
    BUILD_TAGS="kagome icu libstemmer cld2 cznicb leveldb badger" \
    CGO_ENABLED=1 \
    CGO_LDFLAGS="-L/usr/local/opt/icu4c/lib" \
    CGO_CFLAGS="-I/usr/local/opt/icu4c/include" \
    dist

Starting Blast index node

Running a Blast index node is easy. Start Blast data node like so:

$ ./bin/blast-indexer start --node-id=indexer1 --data-dir=/tmp/blast/indexer1 --bind-addr=:6060 --grpc-addr=:5050 --http-addr=:8080 --index-mapping-file=./example/index_mapping.json

Please refer to following document for details of index mapping:

You can now put, get, search and delete the documents via CLI.

Indexing a document via CLI

For document indexing, execute the following command:

$ cat ./example/doc_enwiki_1.json | xargs -0 ./bin/blast-indexer index --grpc-addr=:5050 --id=enwiki_1

You can see the result in JSON format. The result of the above command is:

{
  "count": 1
}

Getting a document via CLI

Getting a document is as following:

$ ./bin/blast-indexer get --grpc-addr=:5050 --id=enwiki_1

You can see the result in JSON format. The result of the above command is:

{
  "_type": "enwiki",
  "contributor": "unknown",
  "text_en": "A search engine is an information retrieval system designed to help find information stored on a computer system. The search results are usually presented in a list and are commonly called hits. Search engines help to minimize the time required to find information and the amount of information which must be consulted, akin to other techniques for managing information overload. The most public, visible form of a search engine is a Web search engine which searches for information on the World Wide Web.",
  "timestamp": "2018-07-04T05:41:00Z",
  "title_en": "Search engine (computing)"
}

Searching documents via CLI

Searching documents is as like following:

$ cat ./example/search_request.json | xargs -0 ./bin/blast-indexer search --grpc-addr=:5050

You can see the result in JSON format. The result of the above command is:

{
  "status": {
    "total": 1,
    "failed": 0,
    "successful": 1
  },
  "request": {
    "query": {
      "query": "+_all:search"
    },
    "size": 10,
    "from": 0,
    "highlight": {
      "style": "html",
      "fields": [
        "title",
        "text"
      ]
    },
    "fields": [
      "*"
    ],
    "facets": {
      "Contributor count": {
        "size": 10,
        "field": "contributor"
      },
      "Timestamp range": {
        "size": 10,
        "field": "timestamp",
        "date_ranges": [
          {
            "end": "2010-12-31T23:59:59Z",
            "name": "2001 - 2010",
            "start": "2001-01-01T00:00:00Z"
          },
          {
            "end": "2020-12-31T23:59:59Z",
            "name": "2011 - 2020",
            "start": "2011-01-01T00:00:00Z"
          }
        ]
      }
    },
    "explain": false,
    "sort": [
      "-_score"
    ],
    "includeLocations": false
  },
  "hits": [
    {
      "index": "/tmp/blast/index1/index",
      "id": "enwiki_1",
      "score": 0.09634961191421738,
      "locations": {
        "text_en": {
          "search": [
            {
              "pos": 2,
              "start": 2,
              "end": 8,
              "array_positions": null
            },
            {
              "pos": 20,
              "start": 118,
              "end": 124,
              "array_positions": null
            },
            {
              "pos": 33,
              "start": 195,
              "end": 201,
              "array_positions": null
            },
            {
              "pos": 68,
              "start": 415,
              "end": 421,
              "array_positions": null
            },
            {
              "pos": 73,
              "start": 438,
              "end": 444,
              "array_positions": null
            },
            {
              "pos": 76,
              "start": 458,
              "end": 466,
              "array_positions": null
            }
          ]
        },
        "title_en": {
          "search": [
            {
              "pos": 1,
              "start": 0,
              "end": 6,
              "array_positions": null
            }
          ]
        }
      },
      "sort": [
        "_score"
      ],
      "fields": {
        "_type": "enwiki",
        "contributor": "unknown",
        "text_en": "A search engine is an information retrieval system designed to help find information stored on a computer system. The search results are usually presented in a list and are commonly called hits. Search engines help to minimize the time required to find information and the amount of information which must be consulted, akin to other techniques for managing information overload. The most public, visible form of a search engine is a Web search engine which searches for information on the World Wide Web.",
        "timestamp": "2018-07-04T05:41:00Z",
        "title_en": "Search engine (computing)"
      }
    }
  ],
  "total_hits": 1,
  "max_score": 0.09634961191421738,
  "took": 362726,
  "facets": {
    "Contributor count": {
      "field": "contributor",
      "total": 1,
      "missing": 0,
      "other": 0,
      "terms": [
        {
          "term": "unknown",
          "count": 1
        }
      ]
    },
    "Timestamp range": {
      "field": "timestamp",
      "total": 1,
      "missing": 0,
      "other": 0,
      "date_ranges": [
        {
          "name": "2011 - 2020",
          "start": "2011-01-01T00:00:00Z",
          "end": "2020-12-31T23:59:59Z",
          "count": 1
        }
      ]
    }
  }
}

Please refer to following document for details of search request and result:

Deleting a document via CLI

Deleting a document is as following:

$ ./bin/blast-indexer delete --grpc-addr=:5050 --id=enwiki_1

You can see the result in JSON format. The result of the above command is:

{
  "count": 1
}

Indexing documents in bulk via CLI

Indexing documents in bulk, run the following command:

$ cat ./example/docs_wiki.json | xargs -0 ./bin/blast-indexer index --grpc-addr=:5050

You can see the result in JSON format. The result of the above command is:

{
  "count": 4
}

Deleting documents in bulk via CLI

Deleting documents in bulk, run the following command:

$ cat ./example/docs_wiki.json | xargs -0 ./bin/blast-indexer delete --grpc-addr=:5050

You can see the result in JSON format. The result of the above command is:

{
  "count": 4
}

Using HTTP REST API

Also you can do above commands via HTTP REST API that listened port 8080.

Indexing a document via HTTP REST API

Indexing a document via HTTP is as following:

$ curl -s -X PUT 'http://127.0.0.1:8080/documents/enwiki_1' -d @./example/doc_enwiki_1.json

Getting a document via HTTP REST API

Getting a document via HTTP is as following:

$ curl -s -X GET 'http://127.0.0.1:8080/documents/enwiki_1'

Searching documents via HTTP REST API

Searching documents via HTTP is as following:

$ curl -X POST 'http://127.0.0.1:8080/search' -d @./example/search_request.json

Deleting a document via HTTP REST API

Deleting a document via HTTP is as following:

$ curl -X DELETE 'http://127.0.0.1:8080/documents/enwiki_1'

Indexing documents in bulk via HTTP REST API

Indexing documents in bulk via HTTP is as following:

$ curl -s -X PUT 'http://127.0.0.1:8080/documents' -d @./example/docs_wiki.json

Deleting documents in bulk via HTTP REST API

Deleting documents in bulk via HTTP is as following:

$ curl -X DELETE 'http://127.0.0.1:8080/documents' -d @./example/docs_wiki.json

Bringing up a cluster

Blast is easy to bring up the cluster. Blast data node is already running, but that is not fault tolerant. If you need to increase the fault tolerance, bring up 2 more data nodes like so:

$ ./bin/blast-indexer start --node-id=indexer2 --data-dir=/tmp/blast/indexer2 --bind-addr=:6061 --grpc-addr=:5051 --http-addr=:8081 --index-mapping-file=./example/index_mapping.json --join-addr=:5050
$ ./bin/blast-indexer start --node-id=indexer3 --data-dir=/tmp/blast/indexer3 --bind-addr=:6062 --grpc-addr=:5052 --http-addr=:8082 --index-mapping-file=./example/index_mapping.json --join-addr=:5050

Above example shows each Blast node running on the same host, so each node must listen on different ports. This would not be necessary if each node ran on a different host.

This instructs each new node to join an existing node, each node recognizes the joining clusters when started.
So you have a 3-node cluster. That way you can tolerate the failure of 1 node. You can check the peers with the following command:

$ ./bin/blast-indexer cluster --grpc-addr=:5050

You can see the result in JSON format. The result of the above command is:

{
  "nodes": [
    {
      "id": "index1",
      "bind_addr": ":6060",
      "grpc_addr": ":5050",
      "http_addr": ":8080",
      "leader": true,
      "data_dir": "/tmp/blast/index1"
    },
    {
      "id": "index2",
      "bind_addr": ":6061",
      "grpc_addr": ":5051",
      "http_addr": ":8081",
      "data_dir": "/tmp/blast/index2"
    },
    {
      "id": "index3",
      "bind_addr": ":6062",
      "grpc_addr": ":5052",
      "http_addr": ":8082",
      "data_dir": "/tmp/blast/index3"
    }
  ]
}

Recommend 3 or more odd number of nodes in the cluster. In failure scenarios, data loss is inevitable, so avoid deploying single nodes.

The following command indexes documents to any node in the cluster:

$ cat ./example/doc_enwiki_1.json | xargs -0 ./bin/blast-indexer index --grpc-addr=:5050 enwiki_1

So, you can get the document from the node specified by the above command as follows:

$ ./bin/blast-indexer get --grpc-addr=:5050 enwiki_1

You can see the result in JSON format. The result of the above command is:

{
  "_type": "enwiki",
  "contributor": "unknown",
  "text_en": "A search engine is an information retrieval system designed to help find information stored on a computer system. The search results are usually presented in a list and are commonly called hits. Search engines help to minimize the time required to find information and the amount of information which must be consulted, akin to other techniques for managing information overload. The most public, visible form of a search engine is a Web search engine which searches for information on the World Wide Web.",
  "timestamp": "2018-07-04T05:41:00Z",
  "title_en": "Search engine (computing)"
}

You can also get the same document from other nodes in the cluster as follows:

$ ./bin/blast-indexer get --grpc-addr=:5051 enwiki_1
$ ./bin/blast-indexer get --grpc-addr=:5052 enwiki_1

You can see the result in JSON format. The result of the above command is:

{
  "_type": "enwiki",
  "contributor": "unknown",
  "text_en": "A search engine is an information retrieval system designed to help find information stored on a computer system. The search results are usually presented in a list and are commonly called hits. Search engines help to minimize the time required to find information and the amount of information which must be consulted, akin to other techniques for managing information overload. The most public, visible form of a search engine is a Web search engine which searches for information on the World Wide Web.",
  "timestamp": "2018-07-04T05:41:00Z",
  "title_en": "Search engine (computing)"
}

Blast on Docker

Building Docker container image on localhost

You can build the Docker container image like so:

$ make docker-build

Pulling Docker container image from docker.io

You can also use the Docker container image already registered in docker.io like so:

$ docker pull mosuka/blast:latest

See https://hub.docker.com/r/mosuka/blast/tags/

Pulling Docker container image from docker.io

You can also use the Docker container image already registered in docker.io like so:

$ docker pull mosuka/blast:latest

Running Blast index node on Docker

Running a Blast data node on Docker. Start Blast data node like so:

$ docker run --rm --name blast-indexer1 \
    -p 5050:5050 \
    -p 6060:6060 \
    -p 8080:8080 \
    -v $(pwd)/example:/opt/blast/example \
    mosuka/blast:latest blast-indexer start \
      --node-id=blast-indexer1 \
      --bind-addr=:6060 \
      --grpc-addr=:5050 \
      --http-addr=:8080 \
      --data-dir=/tmp/blast/indexer1 \
      --index-mapping-file=/opt/blast/example/index_mapping.json \
      --index-storage-type=leveldb

You can execute the command in docker container as follows:

$ docker exec -it blast-indexer1 blast-indexer node --grpc-addr=:5050

Wikipedia example

This section explain how to index Wikipedia dump to Blast.

Install wikiextractor

$ cd ${HOME}
$ git clone [email protected]:attardi/wikiextractor.git

Download wikipedia dump

$ curl -o ~/tmp/enwiki-20190101-pages-articles.xml.bz2 https://dumps.wikimedia.org/enwiki/20190101/enwiki-20190101-pages-articles.xml.bz2

Parsing wikipedia dump

$ cd wikiextractor
$ ./WikiExtractor.py -o ~/tmp/enwiki --json ~/tmp/enwiki-20190101-pages-articles.xml.bz2

Indexing wikipedia dump

$ for FILE in $(find ~/tmp/enwiki -type f -name '*' | sort)
  do
    echo "Indexing ${FILE}"
    TIMESTAMP=$(date -u "+%Y-%m-%dT%H:%M:%SZ")
    DOCS=$(cat ${FILE} | jq -r '. + {fields: {url: .url, title_en: .title, text_en: .text, timestamp: "'${TIMESTAMP}'", _type: "enwiki"}} | del(.url) | del(.title) | del(.text) | del(.fields.id)' | jq -s)
    curl -s -X PUT -H 'Content-Type: application/json' "http://127.0.0.1:8080/documents" -d "${DOCS}"
  done

GitHub