7.3.35. logical_range_filter#
7.3.35.1. Summary#
Added in version 5.0.0.
logical_range_filter is a sharding version of
range_filter. logical_range_filter searches records from
multiple tables and outputs them.
logical_range_filter is similar to logical_select. Both of
them searches records from multiples tables and outputs
them. logical_range_filter stops searching when the number of
matched records is requested the number of
records. logical_select searches all records and outputs only
needed records.
logical_range_filter has performance merit but some restrictions.
If many records are matched and requested records are small,
logical_range_filter will be faster than logical_select.
logical_range_filter doesn’t support drilldown because drilldown
requires all matched records. logical_range_filter may not find
all matched records. So logical_range_filter doesn’t support
drilldown.
logical_range_filter doesn’t return the number of all matched
records. Because logical_range_filter may not search all matched
records.
You need to plugin_register sharding plugin because
this command is included in sharding plugin.
7.3.35.2. Syntax#
This command takes many parameters.
The required parameters are logical_table and shard_key:
logical_range_filter
logical_table
shard_key
[min=null]
[min_border="include"]
[max=null]
[max_border="include"]
[order="ascending"]
[filter=null]
[offset=0]
[limit=10]
[output_columns="_key, *"]
[use_range_index=null]
[post_filter=null]
[sort_keys=null]
There are some parameters that can be only used as named parameters. You can’t use these parameters as ordered parameters. You must specify parameter name.
Here are parameters that can be only used as named parameters:
cache=no
Added in version 7.0.9: This command has the following named parameters for dynamic columns:
columns[${NAME}].stage=null
columns[${NAME}].flags=COLUMN_SCALAR
columns[${NAME}].type=null
columns[${NAME}].value=null
columns[${NAME}].window.sort_keys=null
columns[${NAME}].window.group_keys=null
You can use one or more alphabets, digits, _ for ${NAME}. For
example, column1 is a valid ${NAME}. This is the same rule as
normal column. See also name.
Parameters that have the same ${NAME} are grouped.
For example, the following parameters specify one dynamic column:
--columns[name].stage initial
--columns[name].type UInt32
--columns[name].value 29
The following parameters specify two dynamic columns:
--columns[name1].stage initial
--columns[name1].type UInt32
--columns[name1].value 29
--columns[name2].stage filtered
--columns[name2].type Float
--columns[name2].value '_score * 0.1'
7.3.35.3. Usage#
Let’s learn about usage with examples. This section shows many popular usages.
You need to register sharding plugin because this command is
included in sharding plugin.
Execution example:
plugin_register sharding
# [[0,1337566253.89858,0.000355720520019531],true]
Here are a schema definition and sample data to show usage.
Execution example:
table_create Entries_20150708 TABLE_HASH_KEY ShortText
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Entries_20150708 created_at COLUMN_SCALAR Time
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Entries_20150708 content COLUMN_SCALAR Text
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Entries_20150708 n_likes COLUMN_SCALAR UInt32
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Entries_20150708 tag COLUMN_SCALAR ShortText
# [[0,1337566253.89858,0.000355720520019531],true]
table_create Entries_20150709 TABLE_HASH_KEY ShortText
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Entries_20150709 created_at COLUMN_SCALAR Time
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Entries_20150709 content COLUMN_SCALAR Text
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Entries_20150709 n_likes COLUMN_SCALAR UInt32
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Entries_20150709 tag COLUMN_SCALAR ShortText
# [[0,1337566253.89858,0.000355720520019531],true]
table_create Terms TABLE_PAT_KEY ShortText \
--default_tokenizer TokenBigram \
--normalizer NormalizerAuto
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Terms entries_key_index_20150708 \
COLUMN_INDEX|WITH_POSITION Entries_20150708 _key
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Terms entries_content_index_20150708 \
COLUMN_INDEX|WITH_POSITION Entries_20150708 content
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Terms entries_key_index_20150709 \
COLUMN_INDEX|WITH_POSITION Entries_20150709 _key
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Terms entries_content_index_20150709 \
COLUMN_INDEX|WITH_POSITION Entries_20150709 content
# [[0,1337566253.89858,0.000355720520019531],true]
load --table Entries_20150708
[
{"_key": "The first post!",
"created_at": "2015/07/08 00:00:00",
"content": "Welcome! This is my first post!",
"n_likes": 5,
"tag": "Hello"},
{"_key": "Groonga",
"created_at": "2015/07/08 01:00:00",
"content": "I started to use Groonga. It's very fast!",
"n_likes": 10,
"tag": "Groonga"},
{"_key": "Mroonga",
"created_at": "2015/07/08 02:00:00",
"content": "I also started to use Mroonga. It's also very fast! Really fast!",
"n_likes": 15,
"tag": "Groonga"}
]
# [[0,1337566253.89858,0.000355720520019531],3]
load --table Entries_20150709
[
{"_key": "Good-bye Senna",
"created_at": "2015/07/09 00:00:00",
"content": "I migrated all Senna system!",
"n_likes": 3,
"tag": "Senna"},
{"_key": "Good-bye Tritonn",
"created_at": "2015/07/09 01:00:00",
"content": "I also migrated all Tritonn system!",
"n_likes": 3,
"tag": "Senna"}
]
# [[0,1337566253.89858,0.000355720520019531],2]
There are two tables, Entries_20150708 and Entries_20150709,
for blog entries.
Note
You need to use ${LOGICAL_TABLE_NAME}_${YYYYMMDD} naming rule
for table names. In this example, LOGICAL_TABLE_NAME is
Entries and YYYYMMDD is 20150708 or 20150709.
An entry has title, created time, content, the number of likes for the
entry and tag. Title is key of Entries_YYYYMMDD. Created time is
value of Entries_YYYYMMDD.created_at column. Content is value of
Entries_YYYYMMDD.content column. The number of likes is value of
Entries_YYYYMMDD.n_likes column. Tag is value of
Entries_YYYYMMDD.tag column.
Entries_YYYYMMDD._key column and Entries_YYYYMMDD.content
column are indexed using TokenBigram tokenizer. So both
Entries_YYYYMMDD._key and Entries_YYYYMMDD.content are
fulltext search ready.
OK. The schema and data for examples are ready.
7.3.35.3.1. Simple usage#
TODO
7.3.35.4. Parameters#
This section describes parameters of logical_range_filter.
7.3.35.4.1. Required parameters#
There are required parameters, logical_table and shard_key.
7.3.35.4.1.1. logical_table#
Specifies logical table name. It means table name without
_YYYYMMDD postfix. If you use actual table such as
Entries_20150708, Entries_20150709 and so on, logical table
name is Entries.
Execution example:
logical_range_filter --logical_table Entries --shard_key created_at
# [
# [
# 0,
# 1337566253.89858,
# 0.000355720520019531
# ],
# [
# [
# [
# "_key",
# "ShortText"
# ],
# [
# "content",
# "Text"
# ],
# [
# "created_at",
# "Time"
# ],
# [
# "n_likes",
# "UInt32"
# ],
# [
# "tag",
# "ShortText"
# ]
# ],
# [
# "The first post!",
# "Welcome! This is my first post!",
# 1436281200.0,
# 5,
# "Hello"
# ],
# [
# "Groonga",
# "I started to use Groonga. It's very fast!",
# 1436284800.0,
# 10,
# "Groonga"
# ],
# [
# "Mroonga",
# "I also started to use Mroonga. It's also very fast! Really fast!",
# 1436288400.0,
# 15,
# "Groonga"
# ],
# [
# "Good-bye Senna",
# "I migrated all Senna system!",
# 1436367600.0,
# 3,
# "Senna"
# ],
# [
# "Good-bye Tritonn",
# "I also migrated all Tritonn system!",
# 1436371200.0,
# 3,
# "Senna"
# ]
# ]
# ]
If nonexistent table is specified, an error is returned.
Execution example:
logical_range_filter --logical_table Nonexistent --shard_key created_at
# [
# [
# -22,
# 1337566253.89858,
# 0.000355720520019531,
# "[logical_range_filter] no shard exists: logical_table: <Nonexistent>: shard_key: <created_at>",
# [
# [
# "execute",
# "lib/groonga/plugins/sharding/logical_range_filter.rb",
# 2929
# ]
# ]
# ]
# ]
7.3.35.4.2. Optional parameters#
There are optional parameters.
7.3.35.4.2.1. min#
Specifies the min value of shard_key
TODO: Add examples
7.3.35.4.2.2. min_border#
Specifies whether the min value of borderline must be include or not.
Specify include or exclude as the value of this parameter.
TODO: Add examples
7.3.35.4.2.3. max#
Specifies the max value of shard_key.
TODO: Add examples
7.3.35.4.2.4. max_border#
Specifies whether the max value of borderline must be include or not.
Specify include or exclude as the value of this parameter.
TODO: Add examples
7.3.35.4.2.5. order#
Specifies order of search result.
Specify ascending or descending as the value of this parameter.
If we set ascending in this parameter, search results are sorted by ascending order based on shared_key.
If we set descending in this parameter, search results are sorted by descending order based on shared_key.
Execution example:
logical_range_filter --logical_table Entries --shard_key created_at --order "descending"
# [
# [
# 0,
# 1337566253.89858,
# 0.000355720520019531
# ],
# [
# [
# [
# "_key",
# "ShortText"
# ],
# [
# "content",
# "Text"
# ],
# [
# "created_at",
# "Time"
# ],
# [
# "n_likes",
# "UInt32"
# ],
# [
# "tag",
# "ShortText"
# ]
# ],
# [
# "Good-bye Tritonn",
# "I also migrated all Tritonn system!",
# 1436371200.0,
# 3,
# "Senna"
# ],
# [
# "Good-bye Senna",
# "I migrated all Senna system!",
# 1436367600.0,
# 3,
# "Senna"
# ],
# [
# "Mroonga",
# "I also started to use Mroonga. It's also very fast! Really fast!",
# 1436288400.0,
# 15,
# "Groonga"
# ],
# [
# "Groonga",
# "I started to use Groonga. It's very fast!",
# 1436284800.0,
# 10,
# "Groonga"
# ],
# [
# "The first post!",
# "Welcome! This is my first post!",
# 1436281200.0,
# 5,
# "Hello"
# ]
# ]
# ]
7.3.35.5. Return value#
The command returns a response with the following format:
[
HEADER,
[
COLUMNS,
RECORDS
]
]
If the command fails, error details are in HEADER.
See Output format for HEADER.
COLUMNS describes about output columns specified by
output_columns. It uses the following
format:
[
[COLUMN_NAME_1, COLUMN_TYPE_1],
[COLUMN_NAME_2, COLUMN_TYPE_2],
...,
[COLUMN_NAME_N, COLUMN_TYPE_N]
]
COLUMNS includes one or more output column information. Each
output column information includes the followings:
Column name as string
Column type as string or
null
Column name is extracted from value specified as output_columns.
Column type is Groonga’s type name or null. It doesn’t describe
whether the column value is vector or scalar. You need to determine it
by whether real column value is array or not.
See Data types for type details.
null is used when column value type isn’t determined. For example,
function call in output_columns such as
--output_columns "snippet_html(content)" uses null.
Here is an example of COLUMNS:
[
["_id", "UInt32"],
["_key", "ShortText"],
["n_likes", "UInt32"],
]
RECORDS includes column values for each matched record. Included
records are selected by offset and
limit. It uses the following format:
[
[
RECORD_1_COLUMN_1,
RECORD_1_COLUMN_2,
...,
RECORD_1_COLUMN_N
],
[
RECORD_2_COLUMN_1,
RECORD_2_COLUMN_2,
...,
RECORD_2_COLUMN_N
],
...
[
RECORD_N_COLUMN_1,
RECORD_N_COLUMN_2,
...,
RECORD_N_COLUMN_N
]
]
Here is an example RECORDS:
[
[
1,
"The first post!",
5
],
[
2,
"Groonga",
10
],
[
3,
"Mroonga",
15
]
]