7.3. Command Line Tools

This chapter describes GeoMesa Tools, a set of command line tools for feature management, query planning and explanation, ingest, and export from the command line.

7.3.1. Installing SFT and Converter Definitions

Starting with version 1.2.3, GeoMesa Tools ships with embedded SimpleFeatureType and GeoMesa Converter definitions for common data types including Twitter, GeoNames, T-drive, and many more. See Using SFT and Converter Definitions with Command-Line Tools.

To see which SFT and converter configurations are installed, try the geomesa env command described below.

7.3.2. Running the command line tools

Note

Some command names have changed in GeoMesa 1.3.0; see Updated Command Line Tools

Run geomesa without any arguments to produce the following usage text:

$ geomesa
Usage: geomesa [command] [command options]
  Commands:
    add-attribute-index    Run a Hadoop map reduce job to add an index for attributes
    add-index              Add or update indices for an existing GeoMesa feature type
    classpath              Display the GeoMesa classpath
    config-table           Perform table configuration operations
    configure              Configure the local environment for GeoMesa
    convert                Convert files using GeoMesa's internal SFT converter framework
    create-schema          Create a GeoMesa feature type
    delete-catalog         Delete a GeoMesa catalog completely (and all features in it)
    delete-features        Delete features from a table in GeoMesa. Does not delete any tables or schema information.
    delete-raster          Delete a GeoMesa Raster table
    env                    Examine the current GeoMesa environment
    explain                Explain how a GeoMesa query will be executed
    export                 Export features from a GeoMesa data store
    export-bin             Export features from a GeoMesa data store in a binary format.
    gen-avro-schema        Generate an Avro schema from a SimpleFeatureType
    get-names              List GeoMesa feature types for a given catalog
    get-schema             Describe the attributes of a given GeoMesa feature type
    get-sft-config                Get the SimpleFeatureType of a feature
    help                   Show help
    ingest                 Ingest/convert various file formats into GeoMesa
    ingest-raster          Ingest raster files into GeoMesa
    keywords               Add/Remove/List keywords on an existing schema
    query-raster-stats     Export queries and statistics about the last X number of queries to a CSV file.
    remove-schema          Remove a schema and associated features from a GeoMesa catalog
    stats-analyze          Analyze statistics on a GeoMesa feature type
    stats-bounds           View or calculate bounds on attributes in a GeoMesa feature type
    stats-count            Estimate or calculate feature counts in a GeoMesa feature type
    stats-histogram        View or calculate counts of attribute in a GeoMesa feature type, grouped by sorted values
    stats-top-k            Enumerate the most frequent values in a GeoMesa feature type
    version                Display the installed GeoMesa version

This usage text lists the available commands. To see help for an individual command, run geomesa help <command-name>, which for example will give you something like this:

$ geomesa help get-type-names
Usage: get-type-names [options]
  Options:
    --auths
       Accumulo authorizations
  * -c, --catalog
       Catalog table for GeoMesa datastore
    -i, --instance
       Accumulo instance name
    --keytab
       Path to Accumulo user Kerberos keytab file
    --mock
       Run everything with a mock accumulo instance instead of a real one
       Default: false
    -p, --password
       Accumulo password (will prompt if not supplied and not using Kerberos)
  * -u, --user
       Accumulo user name
    --visibilities
       Default feature visibilities
    -z, --zookeepers
       Zookeepers (host[:port], comma separated)

The Accumulo username and either a password or a path to a Kerberos keytab file is required for each command. Specify the username and password in each command by using -u (or --username) and -p (or --password), respectively. One can also only specify the username on the command line using -u or --username and type the password in an additional prompt, where the password will be hidden from the shell history. To use Kerberos authentication instead, use --keytab with a path to a Kerberos keytab file containing an entry for the specified user. Since a keytab file allows authentication without any further constraints, it should be protected appropriately.

In nearly all commands below, one can add --instance-name, --zookeepers, --auths, and --visibilities (or in short form -i, -z, -a, and -v) arguments to properly configure the Accumulo data store connector. The Accumulo instance name and Zookeepers string can usually be automatically assigned as long as Accumulo is configured correctly. The Auths and Visibilities strings will have to be added as arguments to each command, if needed.

7.3.3. Command overview

7.3.3.1. Tools Configuration

7.3.3.1.1. configure

Used to configure the current environment for using the commandline tools. This is frequently run after the tools are first installed to ensure the environment is configured correctly:

$ geomesa configure

7.3.3.1.2. classpath

Prints out the current classpath configuration:

$ geomesa classpath

7.3.3.2. Creating and deleting feature types

7.3.3.2.1. create-schema

Used to create a feature type (SimpleFeatureType) in a GeoMesa catalog:

$ geomesa create -u username -p password \
  -i instance -z zoo1,zoo2,zoo3 \
  -c test_create \
  -f testing \
  -s fid:String:index=true,dtg:Date,geom:Point:srid=4326 \
  --dtg dtg

7.3.3.2.2. get-schema

Display details about the attributes of a specified feature type:

$ geomesa get-schema -u username -p password -c test_delete -f testing

7.3.3.2.3. get-sft-config

Get the specified feature type as a typesafe config:

$ geomesa get-sft-config -u username -p password -c test_catalog -f test_feature --format typesafe

Get the specified feature type as an encoded feature schema string:

$ geomesa get-sft-config -u username -p password -c test_catalog -f test_feature --format spec

7.3.3.2.4. keywords

Add or remove keywords to a specified schema:: Repeat the -a or -r flags to add or remove multiple keywords The --removeAll option removes all keywords The -l option lists the schema’s keywords following all operations If there is whitespace within a keyword, enclose it in quotes for proper functionality:

$ geomesa keywords -u username -p password \
  -a keywordB -a keywordC -r keywordA -l \
  -i instance -z zoo1,zoo2,zoo3 \
  -c catalog -f featureTypeName

7.3.3.2.5. get-names

List all known feature types in a GeoMesa catalog:

$ geomesa get-names -u username -p password -c test_catalog

7.3.3.2.6. remove-schema

Used to remove a feature type (SimpleFeatureType) in a GeoMesa catalog. This will also delete any feature of that type in the data store:

$ geomesa remove-schema -u username -p password \
  -i instance -z zoo1,zoo2,zoo3 \
  -c test_catalog -f testfeature1
$ geomesa remove-schema -u username -p password \
  -i instance -z zoo1,zoo2,zoo3 \
  -c test_catalog --pattern 'testfeatures\d+'

7.3.3.3. Manipulating data

7.3.3.3.1. convert

Convert files using the internal SFT (SimpleFeatureType) converter framework:

$ geomesa convert -spec example --converter example-csv \
  -F json ./exampledata.csv

$ geomesa convert -s example -C example-csv -F avro --gzip 4 \
  --max-features 10 -o exampleout.avro ./exampledata.csv

Note

Output data has been converted by the internal SFT converters as defined by the provided converter config. This most likely means a new converter config will be required to ingest (or re-convert) the converted data.

7.3.3.4. Ingesting and exporting data

7.3.3.4.1. export

Export GeoMesa features. The “attribute expressions” specified by the -a option are comma-separated expressions in the format:

attribute[=filter_function_expression]|derived-attribute=filter_function_expression

filter_function_expression is an expression of filter function applied to attributes, literals and filter functions, i.e. can be nested.

Example export commands:

$ geomesa export -u username -p password \
  -c test_catalog -f test_feature \
  -a "geom,text,user_name" --format csv \
  -q "include" -m 100
$ geomesa export -u username -p password \
  -c test_catalog -f test_feature \
  -a "geom,text,user_name" --format gml \
  -q "user_name='JohnSmith'"
$ geomesa export -u username -p password \
  -c test_catalog -f test_feature \
  -a "user_name,buf=buffer(geom\, 2)" \
  --format csv -q "[[ user_name like `John%' ] AND [ bbox(geom, 22.1371589, 44.386463, 40.228581, 52.379581, 'EPSG:4326') ]]"

For fine-grained control, query hints can be set using the –hints parameter, in the form key1=value1;key2=value2. See Setting Query Hints and Feature Sampling for more information.

7.3.3.4.2. ingest

Used to convert and ingest data from various file formats as GeoMesa features.

GeoMesa defines several common converter factories for formats such as delimited text (TSV, CSV), fixed width files, JSON, XML, and Avro. New converter factories (e.g. for custom binary formats) can be registered on the classpath using Java SPI. Shapefile ingest is also supported. Files can be either local or in HDFS. You cannot mix target files (e.g. local and HDFS).

Note

The header, if present, is not parsed by ingest for information. It is assumed that all lines are valid entries.

Converters and SFTs are specified in the HOCON format and loaded using the TypeSafe configuration library. They can be referenced by name using the -s and -C args.

To define new converters for the users can package a reference.conf file inside a jar and drop it in the $GEOMESA_ACCUMULO_HOME/lib directory or add config definitions to the $GEOMESA_TOOLS/conf/application.conf file which includes some examples. SFT and Converter specifications should use the path prefixes geomesa.converters.<convertername> and geomesa.sfts.<typename>

For example, here’s a simple CSV file to ingest named example.csv:

FID,Name,Age,LastSeen,Friends,Lat,Lon
23623,Harry,20,2015-05-06,"Will, Mark, Suzan",-100.236523,23
26236,Hermione,25,2015-06-07,"Edward, Bill, Harry",40.232,-53.2356
3233,Severus,30,2015-10-23,"Tom, Riddle, Voldemort",3,-62.23

Note

ID is a reserved word, for a full list of reserved words see Reserved Words.

To ingest this file, a SimpleFeatureType named renegades and a converter named renegades-csv can be placed in the application.conf file:

# cat $GEOMESA_ACCUMULO_HOME/conf/application.conf
geomesa {
  sfts {
    renegades = {
      attributes = [
        { name = "fid",      type = "Integer",      index = false                             }
        { name = "name",     type = "String",       index = true                              }
        { name = "age",      type = "Integer",      index = false                             }
        { name = "lastseen", type = "Date",         index = true                              }
        { name = "friends",  type = "List[String]", index = true                              }
        { name = "geom",     type = "Point",        index = true, srid = 4326, default = true }
      ]
    }
  }
  converters {
    renegades-csv = {
      type   = "delimited-text"
      format = "CSV"
      options {
        skip-lines = 1 //skip the header
      }
      id-field = "toString($fid)"
      fields = [
        { name = "fid",      transform = "$1::int"                 }
        { name = "name",     transform = "$2::string"              }
        { name = "age",      transform = "$3::int"                 }
        { name = "lastseen", transform = "date('YYYY-MM-dd', $4)"  }
        { name = "friends",  transform = "parseList('string', $5)" }
        { name = "lon",      transform = "$6::double"              }
        { name = "lat",      transform = "$7::double"              }
        { name = "geom",     transform = "point($lon, $lat)"       }
      ]
    }
  }
}

The SFT and Converter can be referenced by name and the following commands can ingest the file:

$ geomesa ingest -u username -p password \
  -c geomesa_catalog -i instance --threads 1 \
  -s renegades -C renegades-csv example.csv
# use the Hadoop file system instead
$ geomesa ingest -u username -p password \
  -c geomesa_catalog -i instance \
  -s renegades -C renegades-csv hdfs:///some/hdfs/path/to/example.csv

SFT and Converter configs can also be provided as strings or filenames to the -s and -C arguments. The syntax is very similar to the application.conf and reference.conf format. Config specifications must be nested using the paths geomesa.converters.<convertername> and geomesa.sfts.<typename> as shown below:

# A nested SFT config provided as a string or file to the -s argument specifying
# a type named "renegades"
#
# cat /tmp/renegades.sft
geomesa.sfts.renegades = {
  attributes = [
    { name = "fid",      type = "Integer",      index = false                             }
    { name = "name",     type = "String",       index = true                              }
    { name = "age",      type = "Integer",      index = false                             }
    { name = "lastseen", type = "Date",         index = true                              }
    { name = "friends",  type = "List[String]", index = true                              }
    { name = "geom",     type = "Point",        index = true, srid = 4326, default = true }
  ]
}

Similarly, converter configurations must be nested when passing them directly to the -C argument:

# a nested converter definition
# cat /tmp/renegades.convert
geomesa.converters.renegades-csv = {
  type   = "delimited-text"
  format = "CSV"
  options {
    skip-lines = 0 // don't skip lines in distributed ingest
  }
  id-field = "toString($fid)"
  fields = [
    { name = "fid",      transform = "$1::int"                 }
    { name = "name",     transform = "$2::string"              }
    { name = "age",      transform = "$3::int"                 }
    { name = "lastseen", transform = "date('YYYY-MM-dd', $4)"  }
    { name = "friends",  transform = "parseList('string', $5)" }
    { name = "lon",      transform = "$6::double"              }
    { name = "lat",      transform = "$7::double"              }
    { name = "geom",     transform = "point($lon, $lat)"       }
  ]
}

Using the SFT and Converter config files we can then ingest our csv file with this command:

# ingest command
$ geomesa ingest -u username -p password \
  -c geomesa_catalog -i instance \
  -s /tmp/renegades.sft \
  -C /tmp/renegades.convert hdfs:///some/hdfs/path/to/example.csv

For more documentation on converter configuration, see GeoMesa Convert.

Shape files may also be ingested:

$ geomesa ingest -u username -p password \
  -c test_catalog -f shapeFileFeatureName /some/path/to/file.shp

7.3.3.5. Enabling S3 Ingest

Hadoop ships with implementations of S3-based filesystems, which can be enabled in the Hadoop configuration used with GeoMesa tools. Specifically, GeoMesa tools can perform ingests using both the second-generation (s3n) and third-generation (s3a) filesystems. Edit the $HADOOP_CONF_DIR/core-site.xml file in your Hadoop installation, as shown below (these instructions apply to Hadoop 2.5.0 and higher). Note that you must have the environment variable $HADOOP_MAPRED_HOME set properly in your environment. Some configurations can substitute $HADOOP_PREFIX in the classpath values below.

Warning

AWS credentials are valuable! They pay for services and control read and write protection for data. If you are running GeoMesa on AWS EC2 instances, it is recommended to use the s3a filesystem. With s3a, you can omit the Access Key Id and Secret Access keys from core-site.xml and rely on IAM roles.

For s3a:

<!-- core-site.xml -->
<property>
    <name>mapreduce.application.classpath</name>
    <value>$HADOOP_MAPRED_HOME/share/hadoop/mapreduce/*:$HADOOP_MAPRED_HOME/share/hadoop/mapreduce/lib/*:$HADOOP_MAPRED_HOME/share/hadoop/tools/lib/*</value>
    <description>The classpath specifically for Map-Reduce jobs. This override is needed so that s3 URLs work on Hadoop 2.6.0+</description>
</property>

<!-- OMIT these keys if running on AWS EC2; use IAM roles instead -->
<property>
    <name>fs.s3a.access.key</name>
    <value>XXXX YOURS HERE</value>
</property>
<property>
    <name>fs.s3a.secret.key</name>
    <value>XXXX YOURS HERE</value>
    <description>Valuable credential - do not commit to CM</description>
</property>

After you have enabled S3 in your Hadoop configuration you can ingest with GeoMesa tools. Note that you can still use the Kleene star (*) with S3.:

$ geomesa ingest -u username -p password -c geomesa_catalog -i instance -s yourspec -C convert s3a://bucket/path/file*

For s3n:

<!-- core-site.xml -->
<!-- Note that you need to make sure HADOOP_MAPRED_HOME is set or some other way of getting this on the classpath -->
<property>
    <name>mapreduce.application.classpath</name>
    <value>$HADOOP_MAPRED_HOME/share/hadoop/mapreduce/*:$HADOOP_MAPRED_HOME/share/hadoop/mapreduce/lib/*:$HADOOP_MAPRED_HOME/share/hadoop/tools/lib/*</value>
    <description>The classpath specifically for mapreduce jobs. This override is needed so that s3 URLs work on hadoop 2.6.0+</description>
</property>
<property>
    <name>fs.s3n.impl</name>
    <value>org.apache.hadoop.fs.s3native.NativeS3FileSystem</value>
    <description>Tell hadoop which class to use to access s3 URLs. This change became necessary in hadoop 2.6.0</description>
</property>
<property>
    <name>fs.s3n.awsAccessKeyId</name>
    <value>XXXX YOURS HERE</value>
</property>
<property>
    <name>fs.s3n.awsSecretAccessKey</name>
    <value>XXXX YOURS HERE</value>
</property>

S3n paths are prefixed in hadoop with s3n:// as shown below:

$ geomesa ingest -u username -p password \
  -c geomesa_catalog -i instance -s yourspec \
  -C convert s3n://bucket/path/file s3n://bucket/path/*

7.3.3.6. Enabling Azure Ingest

Hadoop ships with implementations of Azure-based filesystems, which can be enabled in the Hadoop configuration used with GeoMesa tools. Specifically, GeoMesa tools can perform ingests using the (wasb) and (wasbs) filesystems. Edit the $HADOOP_CONF_DIR/core-site.xml file in your Hadoop installation as shown below (these instructions apply to Hadoop 2.5.0 and higher). In addition, the hadoop-azure and azure-storage jars need to be available.

Warning

Azure credentials are valuable! They pay for services and control read and write protection for data. Be sure to keep your core-site.xml configuration file safe. It is recommended that you use Azure’s SSL enable file protocal variant wasbs where possible.

Configuration:

To enable, place the following in your Hadoop Installation’s core-site.xml.

<!-- core-site.xml -->
<property>
  <name>fs.azure.account.key.ACCOUNTNAME.blob.core.windows.net</name>
  <value>XXXX YOUR ACCOUNT KEY</value>
</property>

After you have enabled Azure in your Hadoop configuration you can ingest with GeoMesa tools. Note that you can still use the Kleene star (*) with Azure.:

$ geomesa ingest -u username -p password \
  -c geomesa_catalog -i instance -s yourspec \
  -C convert wasb://CONTAINER@ACCOUNTNAME.blob.core.windows.net/files/*

7.3.3.7. Working with raster data

7.3.3.7.1. delete-raster

Delete a given GeoMesa raster table:

$ geomesa delete-raster -u username -p password -t somerastertable -f

7.3.3.7.2. ingest-raster

Ingest one or multiple raster image files into Geomesa. Input files, GeoTIFF or DTED, should be located on the local file system.

Note

Make sure GDAL is installed when doing chunking, which depends on the GDAL utility gdal_translate.

Input raster files are assumed to have CRS set to EPSG:4326. For non-EPSG:4326 files, they need to be converted into EPSG:4326 raster files before ingestion. An example of doing conversion with GDAL utility is gdalwarp -t_srs EPSG:4326 input_file out_file.

Example usage:

$ geomesa ingest-raster -u username -p password \
  -t geomesa_raster -f /some/local/path/to/raster.tif

7.3.3.7.3. query-rasterstats

Export queries and statistics about the n most recent raster queries to a CSV file:

$ geomesa query-rasterstats -u username -p password -t somerastertable -n 10

7.3.3.8. Performing system administration tasks

7.3.3.8.1. add-index

Add or update indices for an existing feature type. This can be used to upgrade-in-place, converting an older index format into the latest. See Upgrading Existing Indices for more information.

Example usage:

$ geomesa add-index -u username -p password -i instance \
  -z zoo1,zoo2,zoo3 -c test_catalog -f test_feature --index xz3

7.3.3.8.2. delete-catalog

Delete a GeoMesa catalog table completely, along with all features in it.

Example usage:

$ geomesa delete-catalog -u username -p password \
  -i instance -z zoo1,zoo2,zoo3 -c test_catalog

7.3.3.8.3. delete-features

Delete features from a table in GeoMesa. Does not delete any tables or schema information.

Example usage:

$ geomesa delete-features -u username -p password \
  -i instance -z zoo1,zoo2,zoo3 -c test_catalog \
  -q 'dtg DURING 2016-02-02T00:00:00.000Z/2016-02-03T00:00:00.000Z'

7.3.3.8.4. add-attribute-index

Add attribute indices for a specified list of attributes.:

$ geomesa add-attribute-index -u username -p password -i instance -z zoo1,zoo2,zoo3 -c test_catalog \
  -f test_feature -a attribute1,attribute2 --coverage full

This will launch a map-reduce job creating attribute indices for each attribute listed in -a. This is essentially a convenience wrapper for invoking the job described in Attribute Indexing.

7.3.3.8.5. env

Examines the current GeoMesa tools environment, and prints out simple feature types converters that are available on the current classpath. The available types can be used for ingestion; see the ingest command. Use of this command without parameters will result in behavior similar to when the help command is used.

Parameters allow you to specify what to print to out. These give you the ability to view a list of all simple feature types and converters, describe all the feature types and converters, or review a subset of these simple feature types and converters. There are a few options that permit you to specify the desired format when describing simple feature types.

There are a few commands pertaining to the format of describing simple feature types.

Example usage:

$ geomesa env --list-sfts

7.3.3.8.6. explain

Explain how a given GeoMesa query will be executed:

$ geomesa explain -u username -p password \
  -c test_catalog -f test_feature \
  -q "INTERSECTS(geom, POLYGON ((41 28, 42 28, 42 29, 41 29, 41 28)))"

7.3.3.8.7. stats-analyze

Analyze statistics for your data set. This may improve query planning.

Example usage:

$ geomesa stats-analyze -u username -p password -c geomesa.data -f twitter
  Running stat analysis for feature type twitter...
  Stats analyzed:
    Total features: 8852601
    Bounds for geom: [ -171.75, -45.5903996, 157.7302, 89.99997102 ] cardinality: 2119237
    Bounds for dtg: [ '2016-02-01T00:09:12.000Z' to '2016-03-01T00:21:02.000Z' ] cardinality: 2161132
    Bounds for user_id: [ '100000215' to '99999502' ] cardinality: 861283
  Use 'stats-histogram' or 'stats-count' commands for more details

7.3.3.8.8. stats-bounds

Displays the bounds of your data for different attributes. You can use pre-calculated stats for a quick estimation, or get the definitive result by querying the data set using the ‘–no-cache’ flag.

Example usage:

$ geomesa stats-bounds -u username -p password -i instance -z zoo1,zoo2,zoo3 \
    -c geomesa.data -f twitter
  user_id [ 100000215 to 99999502 ] cardinality: 861283
  user_name [ unavailable ]
  text [ unavailable ]
  dtg [ 2016-02-01T00:09:12.000Z to 2016-03-01T00:21:02.000Z ] cardinality: 2161132
  geom [ -171.75, -45.5903996, 157.7302, 89.99997102 ] cardinality: 2119237

$ geomesa stats-bounds -u username -p password -i instance -z zoo1,zoo2,zoo3 \
    -c geomesa.data -f twitter --no-cache \
    -q 'BBOX(geom,-70,45,-60,55) AND dtg DURING 2016-02-02T00:00:00.000Z/2016-02-03T00:00:00.000Z'
  Running stat query...
    user_id [ 1011811424 to 99124417 ] cardinality: 115
    user_name [ bar_user to foo_user ] cardinality: 113
    text [ bar to foo ] cardinality: 180
    dtg [ 2016-02-02T00:01:07.000Z to 2016-02-02T23:59:41.000Z ] cardinality: 178
    geom [ -69.87212338, 45.01259299, -60.08925, 53.8868369 ] cardinality: 155

7.3.3.8.9. stats-count

Counts the features in your data set. You can count total features, or features that match a CQL filter. You can use pre-calculated stats for a quick estimation, or get the definitive result by querying the data set using the ‘–no-cache’ flag.

Example usage:

$ geomesa stats-count -u username -p password -i instance -z zoo1,zoo2,zoo3 \
    -c geomesa.data -f twitter
  Estimated count: 8852601

$ geomesa stats-count -u username -p password -i instance -z zoo1,zoo2,zoo3 \
    -c geomesa.data -f twitter \
    -q 'BBOX(geom,-70,45,-60,55) AND dtg DURING 2016-02-02T00:00:00.000Z/2016-02-03T00:00:00.000Z'
  Estimated count: 2681

$ geomesa stats-count -u username -p password -i instance -z zoo1,zoo2,zoo3 \
    -c geomesa.data -f twitter --no-cache \
    -q 'BBOX(geom,-70,45,-60,55) AND dtg DURING 2016-02-02T00:00:00.000Z/2016-02-03T00:00:00.000Z'
  Running stat query...
  Count: 182

7.3.3.8.10. stats-top-k

Enumerates the values for attributes in your data set. You can enumerate all values for all features, or only values for features that match a CQL filter.

Example usage:

$ geomesa stats-top-k -u username -p password -i instance -z zoo1,zoo2,zoo3 \
    -c geomesa.data -f twitter -a user_id -k 10
  Top values for 'user_id':
    3144822634 (26681)
    388009236 (20553)
    497145453 (19858)
    563319506 (15848)
    2841269945 (15763)
    2924224280 (15731)
    141302910 (15240)
    2587789764 (14811)
    56266341 (14487)
    889599440 (14330)

7.3.3.8.11. stats-histogram

Counts the features in your data set, grouped into sorted bins. You may specify the number of bins to group attribute into. You can count total features, or features that match a CQL filter. You can use pre-calculated stats for a quick estimation, or get the definitive result by querying the data set using the ‘–no-cache’ flag.

If you query a histogram for a geometry attribute, the result will be displayed in an ASCII heatmap.

Example usage:

$ geomesa stats-histogram -u username -p password -i instance -z zoo1,zoo2,zoo3 \
    -c geomesa.data -f twitter -a dtg --bins 10
  Binned histogram for 'dtg':
    [ 2016-02-01T00:09:12.000Z to 2016-02-03T21:46:23.000Z ] 798968
    [ 2016-02-03T21:46:23.000Z to 2016-02-06T19:23:34.000Z ] 868019
    [ 2016-02-06T19:23:34.000Z to 2016-02-09T17:00:45.000Z ] 861720
    [ 2016-02-09T17:00:45.000Z to 2016-02-12T14:37:56.000Z ] 833473
    [ 2016-02-12T14:37:56.000Z to 2016-02-15T12:15:07.000Z ] 990292
    [ 2016-02-15T12:15:07.000Z to 2016-02-18T09:52:18.000Z ] 842434
    [ 2016-02-18T09:52:18.000Z to 2016-02-21T07:29:29.000Z ] 968936
    [ 2016-02-21T07:29:29.000Z to 2016-02-24T05:06:40.000Z ] 862808
    [ 2016-02-24T05:06:40.000Z to 2016-02-27T02:43:51.000Z ] 869208
    [ 2016-02-27T02:43:51.000Z to 2016-03-01T00:21:02.000Z ] 956743

$ geomesa stats-histogram -u username -p password -i instance -z zoo1,zoo2,zoo3 \
    -c geomesa.data -f twitter -a dtg --bins 10 --no-cache
  Running stat query...
  Binned histogram for 'dtg':
    [ 2016-02-01T00:09:12.000Z to 2016-02-03T21:46:23.000Z ] 805620
    [ 2016-02-03T21:46:23.000Z to 2016-02-06T19:23:34.000Z ] 869361
    [ 2016-02-06T19:23:34.000Z to 2016-02-09T17:00:45.000Z ] 859868
    [ 2016-02-09T17:00:45.000Z to 2016-02-12T14:37:56.000Z ] 832458
    [ 2016-02-12T14:37:56.000Z to 2016-02-15T12:15:07.000Z ] 986829
    [ 2016-02-15T12:15:07.000Z to 2016-02-18T09:52:18.000Z ] 841580
    [ 2016-02-18T09:52:18.000Z to 2016-02-21T07:29:29.000Z ] 970460
    [ 2016-02-21T07:29:29.000Z to 2016-02-24T05:06:40.000Z ] 863484
    [ 2016-02-24T05:06:40.000Z to 2016-02-27T02:43:51.000Z ] 871742
    [ 2016-02-27T02:43:51.000Z to 2016-03-01T00:21:02.000Z ] 951199

7.3.3.8.12. config-table

Perform various table configuration tasks. There are three sub-arguments:

  • list - List the configuration options for a GeoMesa table
  • describe - Describe a given configuration option for a table
  • update - Update a given configuration option for a table

Example commands:

$ geomesa config-table list -u username -p password \
  -c test_catalog -f test_feature -t st_idx
$ geomesa config-table describe -u username -p password \
  -c test_catalog -f test_feature -t attr_idx \
  --param table.bloom.enabled
$ geomesa config-table update -u username -p password \
  -c test_catalog -f test_feature -t records \
  --param table.bloom.enabled -n true

7.3.3.8.13. version

Prints out the version, git branch, and commit ID that the tools were built with:

$ geomesa version