For example if I have the following flat buffer schema:
table table_1 {
field1:uint32_t;
field2:uint32_t;
}
table table_2 {
field3:string;
field4:table_1;
}
root_type table_2;
Is there a way to automatically generate the Json file:
{
"field3": "",
"field4": {
"field1":"",
"field2":""
}
}
So it will be easier to fill the Json file and generate a bin file.
I just need to implement a reader and not a builder.
Thanks
There is no built-in way, but you could use the reflection API to do it yourself. Generate the binary schema using flatc, read in that binary schema into your own application and iterate over the tables and fields and export it as JSON.
I recently wrote a Lua generator that follows this scheme, and you could something very similar.
Related
I have a custom schema, stored in a json file. I want to parse that schema. Unfortunately, that schema is an enterprise product, so I cannot find a way to parse it. Any approach how to parse a custom schema, I am quite stuck at this point.
One of the example of such schema is following:
{
typeid:org.name:prop1.0.0,
properties : {
typevalue:Float64,
length:4,
typeid:element,
description:"List to store elements"
}
}
One thing I was able to figure out that the typeid is analogous to $id in json-schema. So I think I can parse that. But I am unsure about the others.
I am using Audit.Net library to log EntityFramework actions into a database (currently everything into one AuditEventLogs table, where the JsonData column stores the data in the following Json format:
{
"EventType":"MyDbContext:test_database",
"StartDate":"2021-06-24T12:11:59.4578873Z",
"EndDate":"2021-06-24T12:11:59.4862278Z",
"Duration":28,
"EntityFrameworkEvent":{
"Database":"test_database",
"Entries":[
{
"Table":"Offices",
"Name":"Office",
"Action":"Update",
"PrimaryKey":{
"Id":"40b5egc7-46ca-429b-86cb-3b0781d360c8"
},
"Changes":[
{
"ColumnName":"Address",
"OriginalValue":"test_address",
"NewValue":"test_address"
},
{
"ColumnName":"Contact",
"OriginalValue":"test_contact",
"NewValue":"test_contact"
},
{
"ColumnName":"Email",
"OriginalValue":"test_email",
"NewValue":"test_email2"
},
{
"ColumnName":"Name",
"OriginalValue":"test_name",
"NewValue":"test_name"
},
{
"ColumnName":"OfficeSector",
"OriginalValue":1,
"NewValue":1
},
{
"ColumnName":"PhoneNumber",
"OriginalValue":"test_phoneNumber",
"NewValue":"test_phoneNumber"
}
],
"ColumnValues":{
"Id":"40b5egc7-46ca-429b-86cb-3b0781d360c8",
"Address":"test_address",
"Contact":"test_contact",
"Email":"test_email2",
"Name":"test_name",
"OfficeSector":1,
"PhoneNumber":"test_phoneNumber"
},
"Valid":true
}
],
"Result":1,
"Success":true
}
}
Me and my team has a main aspect to achieve:
Being able to create a search page where administrators are able to tell
who changed
what did they change
when did the change happen
They can give a time period, to reduce the number of audit records, and the interesting part comes here:
There should be an input text field which should let them search in the values of the "ColumnValues" section.
The problems I encountered:
Even if I map the Json structure into relational rows, I am unable to search in every column, with keeping the genericity.
If I don't map, I could search in the Json string with LIKE mssql function but on the order of a few 100,000 records it takes an eternity for the query to finish so it is probably not the way.
Keeping the genericity would be important, so we don't need to modify the audit search page every time when we create or modify a new entity.
I only know MSSQL, but is it possible that storing the audit logs in a document oriented database like cosmosDB (or anything else, it was just an example) would solve my problem? Or can I reach the desired behaviour using relational database like MSSQL?
Looks like you're asking for an opinion, in that case I would strongly recommend a document oriented DB.
CosmosDB could be a great option since it supports SQL queries.
There is an extension to log to CosmosDB from Audit.NET: Audit.AzureCosmos
A sample query:
SELECT c.EventType, e.Table, e.Action, ch.ColumnName, ch.OriginalValue, ch.NewValue
FROM c
JOIN e IN c.EntityFrameworkEvent.Entries
JOIN ch IN e.Changes
WHERE ch.ColumnName = "Address" AND ch.OriginalValue = "test_address"
Here is a nice post with lot of examples of complex SQL queries on CosmosDB
I have some data on ElasticSearch that I need to send on HDFS. I'm trying to use pig (this is the first time I'm using it), but I have some problem to define a correct schema for my data.
First of all, I tried loading a JSON using the option 'es.output.json=true' with org.elasticsearch.hadoop.pig.EsStorage, and I can load/dump data correctly, and also save them as a JSON to HDFS using STORE A INTO 'hdfs://path/to/store';. Later, defining an external table on HIVE, I can query this data. This is the full example that is working fine (I removed all SSL attributes from the code):
REGISTER /path/to/commons-httpclient-3.1.jar;
REGISTER /path/to/elasticsearch-hadoop-5.3.0.jar;
A = LOAD 'my-index/log' USING org.elasticsearch.hadoop.pig.EsStorage(
'es.nodes=https://addr1:port,https://addr2:port2,https://addr3:port3',
'es.query=?q=*',
'es.output.json=true');
STORE A INTO 'hdfs://path/to/store';
How can I store my data as AVRO to HDFS? I suppose I need to use AvroStorage, but I should also define a schema loading the data, or the JSON is enough? I tried to define a schema with LOAD...USING...AS command and setting es.mapping.date.rich=false instead of es.output.json=true (my data is quite complex, with map of maps and things like that), but it doesn't work. I'm not sure if the problem is on the syntax, or in the approach itself. Would be nice to have an hint on the correct direction to follow.
UPDATE
This is an example of what I tried with es.mapping.date.rich=false. My problem is that if a field is null, all fields will be in a wrong order.
A = LOAD 'my-index/log' USING org.elasticsearch.hadoop.pig.EsStorage(
'es.nodes=https://addr1:port,https://addr2:port2,https://addr3:port3',
'es.query=?q=*',
'es.mapping.date.rich=false')
AS(
field1:chararray,
field2:chararray,
field3:map[chararray,fieldMap:map[],chararray],
field4:chararray,
field5:map[]
);
B = FOREACH A GENERATE field1, field2;
STORE B INTO 'hdfs://path/to/store' USING AvroStorage('
{
"type" : "foo1",
"name" : "foo2",
"namespace" : "foo3",
"fields" : [ {
"name" : "field1",
"type" : ["null","string"],
"default" : null
}, {
"name" : "field2",
"type" : ["null","string"],
"default" : null
} ]
}
');
For future readers, I decided to use spark instead as it is much faster than pig. To save avro files on hdfs, I'm using the databrick library.
Trying to generate JSON schema (http://jsonschema.net) from the syncthing (https://docs.syncthing.net/rest/system-connections-get.html) JSON below.
The problem is that the connection objects start with their ID (e.g.
YZJBJFX-RDB...) which is interpreted as a type.
Is it the JSON from synching that isn't standard or is it the issue with the schema generator?
Do you have any suggestions how to get around this if schema generation is a requirement (I.e. no typing schemas manually).
{
"total":{
"paused":false,
"clientVersion":"",
"at":"2015-11-07T17:29:47.691637262+01:00",
"connected":false,
"inBytesTotal":1479,
"type":"",
"outBytesTotal":1318,
"address":""
},
"connections":{
"YZJBJFX-RDBL7WY-6ZGKJ2D-4MJB4E7-ZATSDUY-LD6Y3L3-MLFUYWE-AEMXJAC":{
"connected":true,
"inBytesTotal":556,
"paused":false,
"at":"2015-11-07T17:29:47.691548971+01:00",
"clientVersion":"v0.12.1",
"address":"127.0.0.1:22002",
"type":"TCP (Client)",
"outBytesTotal":550
},
"DOVII4U-SQEEESM-VZ2CVTC-CJM4YN5-QNV7DCU-5U3ASRL-YVFG6TH-W5DV5AA":{
"outBytesTotal":0,
"type":"",
"address":"",
"at":"0001-01-01T00:00:00Z",
"clientVersion":"",
"paused":false,
"inBytesTotal":0,
"connected":false
},
"UYGDMA4-TPHOFO5-2VQYDCC-7CWX7XW-INZINQT-LE4B42N-4JUZTSM-IWCSXA4":{
"address":"",
"type":"",
"outBytesTotal":0,
"connected":false,
"inBytesTotal":0,
"paused":false,
"at":"0001-01-01T00:00:00Z",
"clientVersion":""
}
}
}
Any input is appreciated.
Is it the JSON from synching that isn't standard or is it the issue
with the schema generator?
There is nothing non-standard about this JSON. Neither is there any issue with the schema generation.
Unfortunately, defining a schema for what is effectively dynamic content is difficult. This will always be the case because the job of schemas is to describe static data structures.
That said, it may be possible to do this using the patternProperties field in JSON schema. This post is effectively asking the same question as yours.
I would like to achieve the following:
My input data looks as follows
{"metadata":
{
"producerName":"capture_api",
"producerVersion":"3.0.13"
},
"payload":
{
--some payload
}
}
I would like to bucket this data using a pig script as follows
/finalOutputDir/producerName/producerVersion/File.txt
Is there a way I can do this. I have tried using the MultiStorage Function but that class supports only one field. I can override the functionality inside multistage but just wanted to check if there is a easier option.
The piggybank MultiStorage could separate the data into multiple folders by a (only one?) field.
STORE data INTO '$out/$producerName' USING org.apache.pig.piggybank.storage.MultiStorage('$out/$producerName', '0', 'none', ',');