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From Christian Link <christian.l...@mdmp.com>
Subject Re: how to load json with nested array into hive?
Date Tue, 24 Jun 2014 10:11:27 GMT
I've got 1.1.9.2 (thanks to Roberto) and the data is looking better...
I'll test the "doubel/int" thingie, now.

Best,
Chris


On Mon, Jun 23, 2014 at 8:51 PM, Swagatika Tripathy <swagatikat856@gmail.com
> wrote:

> Hi,
> Use 1.9.3 Jason serde with dependencies jar. Its the latest one I suppose.
>
> Thanks
> Swagatika
> On Jun 23, 2014 11:57 PM, "Roberto Congiu" <roberto.congiu@openx.com>
> wrote:
>
>> Hi,
>> 1.1.4 is a oldish version of the JSON serde, have you tried with the most
>> recent from the master branch ?
>>
>>
>> On Mon, Jun 23, 2014 at 10:23 AM, Christian Link <christian.link@mdmp.com
>> > wrote:
>>
>>> Hi,
>>>
>>> thanks...but I need to sort things out with ONE SerDe/strategy...
>>> I've started with André's idea by using Roberto Congiu's SerDe and
>>> André's template to create a table with the right schema and loading the
>>> data aftrerwards.
>>>
>>> But it's not completely working...
>>>
>>> I did the following (sorry for spaming...):
>>>
>>> 1. create table and load data
>>>
>>> -- create database (if not exists)
>>> CREATE DATABASE IF NOT EXISTS mdmp_api_dump;
>>>
>>> -- connect to database;
>>> USE mdmp_api_dump;
>>>
>>> -- add SerDE for json processing
>>> ADD JAR /home/hadoop/lib/hive/json-serde-1.1.4-jar-with-dependencies.jar;
>>>
>>> -- drop old raw data
>>> DROP TABLE IF EXISTS mdmp_raw_data;
>>>
>>> -- create raw data table
>>> CREATE TABLE mdmp_raw_data (
>>>   action string,
>>>   batch array<
>>>           struct<
>>>             timestamp:string,
>>>             traits:map<string,string>,
>>>             requestId:string,
>>>             sessionId:string,
>>>             event:string,
>>>             userId:string,
>>>             action:string,
>>>             context:map<string,string>,
>>>             properties:map<string,string>
>>>
>>>           >
>>>         >,
>>>   context struct<
>>>             build:map<string,string>,
>>>             device:struct<
>>>                      brand:string,
>>>                      manufacturer:string,
>>>                      model:string,
>>>                      release:string,
>>>                      sdk:int
>>>                    >,
>>>             display:struct<
>>>                       density:double,
>>>                       height:int,
>>>                       width:int
>>>                     >,
>>>             integrations:map<string,boolean>,
>>>             library:string,
>>>             libraryVersion:string,
>>>             locale:map<string,string>,
>>>             location:map<string,string>,
>>>             telephony:map<string,string>,
>>>             wifi:map<string,boolean>
>>>           >,
>>>   received_at string,
>>>   requestTimestamp string,
>>>   writeKey string
>>> )
>>> ROW FORMAT SERDE 'org.openx.data.jsonserde.JsonSerDe'
>>> STORED AS TEXTFILE;
>>>
>>> -- load data
>>> LOAD DATA INPATH 'hdfs:///input-api/1403181319.json' OVERWRITE INTO
>>> TABLE `mdmp_raw_data`;
>>>
>>> 2. run query against the "raw data" and create "formatted table":
>>>
>>> ADD JAR /home/hadoop/lib/hive/json-serde-1.1.4-jar-with-dependencies.jar;
>>>
>>> USE mdmp_api_dump;
>>>
>>> DROP TABLE IF EXISTS mdmp_api_data;
>>>
>>> CREATE TABLE mdmp_api_data AS
>>> SELECT DISTINCT
>>>   a.action,
>>>   a.received_at,
>>>   a.requestTimestamp,
>>>   a.writeKey,
>>>   a.context.device.brand as brand,
>>>   a.context.device.manufacturer as manufacturer,
>>>   a.context.device.model as model,
>>>   a.context.device.release as release,
>>>   a.context.device.sdk as sdk,
>>> --  a.context.display.density as density,
>>>   a.context.display.height as height,
>>>   a.context.display.width as width,
>>>   a.context.telephony['radio'] as tel_radio,
>>>   a.context.telephony['carrier'] as tel_carrier,
>>>   a.context.wifi['connected'] as wifi_connected,
>>>   a.context.wifi['available'] as wifi_available,
>>>    a.context.locale['carrier'] as loce_carrier,
>>>   a.context.locale['language'] as loce_language,
>>>   a.context.locale['country'] as loce_country,
>>>   a.context.integrations['Tapstream'] as int_tapstream,
>>>   a.context.integrations['Amplitude'] as int_amplitude,
>>>   a.context.integrations['Localytics'] as int_localytics,
>>>   a.context.integrations['Flurry'] as int_flurry,
>>>   a.context.integrations['Countly'] as int_countly,
>>>   a.context.integrations['Quantcast'] as int_quantcast,
>>>   a.context.integrations['Crittercism'] as int_crittercism,
>>>   a.context.integrations['Google Analytics'] as int_googleanalytics,
>>>   a.context.integrations['Mixpanel'] as int_mixpanel,
>>>   b.batch.action AS b_action,
>>>   b.batch.context,
>>>   b.batch.event,
>>>   b.batch.properties,
>>>   b.batch.requestId,
>>>   b.batch.sessionId,
>>>   b.batch.timestamp,
>>>   b.batch.traits,
>>>   b.batch.userId
>>> FROM mdmp_raw_data a
>>> LATERAL VIEW explode(a.batch) b AS batch;
>>>
>>> So far so good... (besides a silly double/int bug in the outdated SerDe)
>>> I thought.
>>>
>>> But it turned out, that some fields are NULL - within all records.
>>>
>>> Affected fields are:
>>>   b.batch.event,
>>>   b.batch.requestId,
>>>   b.batch.sessionId,
>>>   b.batch.userId
>>>
>>> I can see values in the json file, but neither  in the "raw table" nor
>>> in the final table...that's really strange.
>>>
>>> An example record:
>>> {"requestTimestamp":"2014-06-19T14:25:26+02:00","context":{"libraryVersion":"0.6.13","telephony":{"radio":"gsm","carrier":"o2
>>> -
>>> de"},"wifi":{"connected":true,"available":true},"location":{},"locale":{"carrier":"o2
>>> -
>>> de","language":"Deutsch","country":"Deutschland"},"library":"analytics-android","device":{"brand":"htc","model":"HTC
>>> One
>>> S","sdk":16,"release":"4.1.1","manufacturer":"HTC"},"display":{"density":1.5,"width":540,"height":960},"build":{"name":"1.0","code":1},"integrations":{"Tapstream":false,"Amplitude":false,"Localytics":false,"Flurry":false,"Countly":false,"Bugsnag":false,"Quantcast":false,"Crittercism":false,"Google
>>> Analytics":false,"Mixpanel":false}},"batch":[{"timestamp":"2014-06-19T14:25:17+02:00","requestId":"32377337-3f99-4ac5-bfc6-d3654584655b","sessionId":"75cd18db8a364c2","event":"TEST
>>> Doge
>>> Comments","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"comment":"Ruff
>>> ruff!"}},{"timestamp":"2014-06-19T14:25:18+02:00","requestId":"fbfd45c9-cf0f-4cb3-955c-85c65220a5bd","sessionId":"75cd18db8a364c2","event":"TEST
>>> Doge
>>> Purchase","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"revenue":"0,08"}},{"timestamp":"2014-06-19T14:25:18+02:00","requestId":"3a643b12-64e5-4a7c-b44b-e3e09dbc5b66","sessionId":"75cd18db8a364c2","event":"TEST
>>> Doge
>>> Comments","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"comment":"Wow..."}},{"action":"identify","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"timestamp":"2014-06-19T14:25:19+02:00","traits":{"email":"
>>> doges@mdmp.com","name":"Carmelo
>>> Doge"},"requestId":"ef2910f4-cd4f-4175-89d0-7d91b35c229f","sessionId":"75cd18db8a364c2","userId":"doge74167705ruffruff"},{"timestamp":"2014-06-19T14:25:19+02:00","requestId":"1676bb06-abee-4135-a206-d57c4a1bc24d","sessionId":"75cd18db8a364c2","event":"TEST
>>> Doge App
>>> Usage","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{}},{"timestamp":"2014-06-19T14:25:20+02:00","requestId":"66532c8a-c5da-4852-b8b6-04df8f3052d5","sessionId":"75cd18db8a364c2","event":"TEST
>>> Doge
>>> Comments","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"comment":"Many
>>> data."}},{"timestamp":"2014-06-19T14:25:21+02:00","requestId":"a1a79d8c-fe58-4567-8dec-a8d1d2ae2713","sessionId":"75cd18db8a364c2","event":"TEST
>>> Doge
>>> Purchase","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"revenue":"0,87"}},{"timestamp":"2014-06-19T14:25:21+02:00","requestId":"259209ac-b135-4d5f-bdac-535eccc0400e","sessionId":"75cd18db8a364c2","event":"TEST
>>> Doge
>>> Comments","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"comment":"Wow..."}},{"timestamp":"2014-06-19T14:25:23+02:00","requestId":"59b6d57c-c7a5-4b2a-af6d-fa10ae0de60c","sessionId":"75cd18db8a364c2","event":"TEST
>>> Doge
>>> Comments","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"comment":"Such
>>> App!"}},{"timestamp":"2014-06-19T14:25:24+02:00","requestId":"8b05226f-bdf5-4af8-bb91-84da1b874c6e","sessionId":"75cd18db8a364c2","event":"TEST
>>> Doge
>>> Purchase","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"revenue":"0,50"}},{"timestamp":"2014-06-19T14:25:24+02:00","requestId":"0f366675-5641-4238-b2a9-176735de6edd","sessionId":"75cd18db8a364c2","event":"TEST
>>> Doge
>>> Comments","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"comment":"Ruff
>>> ruff!"}},{"timestamp":"2014-06-19T14:25:26+02:00","requestId":"9e832534-5114-4ec1-bc20-1dcf1c354d0c","sessionId":"75cd18db8a364c2","event":"Session
>>> end","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"start":"14:25:09","end":"14:25:26"}}],"writeKey":"a8RCFSAVjmT5qyxLKMzt12kcXWOIusvw","action":"import","received_at":"2014-06-19T12:25:29.790+00:00"}
>>>
>>>
>>> Funny thing is, that I'm sure that I've seen these values earlier
>>> today...I've reloaded the data/tables several times to see if this is still
>>> working...well. :)
>>>
>>> I'm gonna stop for today...another try tomorrow.
>>>
>>> Thanks so far and many greetings from Berlin,
>>> Chris
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>> On Mon, Jun 23, 2014 at 6:57 PM, Sachin Goyal <sgoyal@walmartlabs.com>
>>> wrote:
>>>
>>>>
>>>> You can also use hive-json-schema to automate Hive schema generation
>>>> from JSON:
>>>> https://github.com/quux00/hive-json-schema
>>>>
>>>>
>>>> From: Nitin Pawar <nitinpawar432@gmail.com<mailto:
>>>> nitinpawar432@gmail.com>>
>>>> Reply-To: "user@hive.apache.org<mailto:user@hive.apache.org>" <
>>>> user@hive.apache.org<mailto:user@hive.apache.org>>
>>>> Date: Monday, June 23, 2014 at 2:25 AM
>>>> To: "user@hive.apache.org<mailto:user@hive.apache.org>" <
>>>> user@hive.apache.org<mailto:user@hive.apache.org>>
>>>> Subject: Re: how to load json with nested array into hive?
>>>>
>>>> I think you can just take a look at jsonserde
>>>>
>>>> It does take care of nested json documents. (though you will need to
>>>> know entire json structure upfront)
>>>>
>>>> Here is example of using it
>>>> http://blog.cloudera.com/blog/2012/12/how-to-use-a-serde-in-apache-hive/
>>>>
>>>>
>>>>
>>>>
>>>> On Mon, Jun 23, 2014 at 2:28 PM, Christian Link <
>>>> christian.link@mdmp.com<mailto:christian.link@mdmp.com>> wrote:
>>>> Hi Jerome,
>>>>
>>>> thanks...I've already found "Brickhouse" and the Hive UDFs, but it
>>>> didn't help.
>>>>
>>>> Today I'll try again to process the json file after going through all
>>>> my mails...maybe I'll find a solution.
>>>>
>>>> Best,
>>>> Chris
>>>>
>>>>
>>>> On Fri, Jun 20, 2014 at 7:16 PM, Jerome Banks <jbanks@tagged.com
>>>> <mailto:jbanks@tagged.com>> wrote:
>>>> Christian,
>>>>    Sorry to spam this newsgroup, and this is not a commercial
>>>> endorsement, but check out the Hive UDFs in the Brickhouse project (
>>>> http://github.com/klout/brickhouse ) (
>>>> http://brickhouseconfessions.wordpress.com/2014/02/07/hive-and-json-made-simple/
>>>> )
>>>>
>>>> You can convert arbitrary complex Hive structures to an from json with
>>>> it's to_json and from_json UDF's. See the blog posting for an explanation.
>>>>
>>>> -- jerome
>>>>
>>>>
>>>> On Fri, Jun 20, 2014 at 8:26 AM, Christian Link <
>>>> christian.link@mdmp.com<mailto:christian.link@mdmp.com>> wrote:
>>>> hi,
>>>>
>>>> I'm very, very new to Hadoop, Hive, etc. and I have to import data into
>>>> hive tables.
>>>>
>>>> Environment: Amazon EMR, S3, etc.
>>>>
>>>> The input file is on S3 and I copied it into my HDFS.
>>>>
>>>> 1. flat table with one column and loaded data into it:
>>>>
>>>>   CREATE TABLE mdmp_raw_data (json_record STRING);
>>>>   LOAD DATA INPATH 'hdfs:///input-api/1403181319.json' OVERWRITE INTO
>>>> TABLE `mdmp_raw_data`;
>>>> That worked, I can access some data, like this:
>>>>
>>>> SELECT d.carrier, d.language, d.country
>>>>   FROM mdmp_raw_data a LATERAL VIEW json_tuple(a.data,
>>>> 'requestTimestamp', 'context') b    AS requestTimestamp, context
>>>>   LATERAL VIEW json_tuple(b.context, 'locale') c AS locale
>>>>   LATERAL VIEW json_tuple(c.locale, 'carrier', 'language', 'country') d
>>>> AS carrier, language, country
>>>>   LIMIT 1;
>>>>
>>>> Result: o2 - de Deutsch Deutschland
>>>>
>>>> I can also select the array at once:
>>>>
>>>> SELECT b.requestTimestamp, b.batch
>>>>   FROM mdmp_raw_data a
>>>>   LATERAL VIEW json_tuple(a.data, 'requestTimestamp', 'batch') b AS
>>>> requestTimestamp, batch
>>>>   LIMIT 1;
>>>> This will give me:
>>>>
>>>>  [{"timestamp":"2014-06-19T14:25:18+02:00","requestId":"2ca08247-5542-4cb4-be7e-4a8574fb77a8","sessionId":"f29ec175ca6b7d10","event":"TEST
>>>> Doge
>>>> Comments","userId":"doge96514016ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"comment":"Much
>>>> joy."}}, ...]
>>>>
>>>> This "batch" may contain n events will a structure like above.
>>>>
>>>> I want to put all events in a table where each "element" will be stored
>>>> in a unique column: timestamp, requestId, sessionId, event, userId, action,
>>>> context, properties
>>>>
>>>> 2. explode the "batch" I read a lot about SerDe, etc. - but I don't get
>>>> it.
>>>>
>>>> - I tried to create a table with an array and load the data into it -
>>>> several errors
>>>> use explode in query but it doesn't accept "batch" as array
>>>> - integrated several SerDes but get things like "unknown function
>>>> jspilt"
>>>> - I'm lost in too many documents, howtos, etc. and could need some
>>>> advices...
>>>>
>>>> Thank you in advance!
>>>>
>>>> Best, Chris
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> --
>>>> Nitin Pawar
>>>>
>>>
>>>
>>
>>
>> --
>> ----------------------------------------------------------
>> Good judgement comes with experience.
>> Experience comes with bad judgement.
>> ----------------------------------------------------------
>> Roberto Congiu - Data Engineer - OpenX
>> tel: +1 626 466 1141
>>
>

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