Json file aggregations and transformations to .csv
I have JSON data structured like this:
[
"eventName": "unmuteClick",
"intPayload":0,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099009,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "muteClick",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099009,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "resumeClick",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 15416320990586,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "pauseClick",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 15416320990585,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "mediaDuration",
"intPayload":10000,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "firstQuartileCount",
"intPayload": 1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "secondQuartileCount",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "thirdQuartileCount",
"intPayload":0,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "completeCount",
"intPayload":0,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v"
]
Each record is a different event that can happen during video playback. One video playback has a unique playbackId, so you can see there are 10 events related to the same playback.
What I need to do is aggregate and transform this data to CSV format, where each row would be aggregated results for one playbackId.
I need to transform the values in the eventName field into columns, where the values in the intPayload field are the values of the columns.
Here is the schema I need to use:
playbackId, sessionId, pageAsin, videoAsin, unmuteClick,muteClick, pauseClick, resumeClick, mediaDuration,firstQuartileCount, secondQuartileCount,thirdQuartileCount,completeCount
Based on the data, values for the schema would be like this:
"49309k-54353esfs-resf43-23fs43jk","324435-65657-3256-8787", "B00K7GXXKQ", "B078LXG579v",1,1,1,1,10000,1,1,0,0"
(For the same playbackId, fields like sessionId, pageAsin and videoAsin would be the same.)
Does anything already exist for transformations and aggregations like this? Can I use Elastic Map reduce for calculations like this? The input data size is pretty large.
json amazon-web-services mapreduce aggregate amazon-emr
edited Nov 14 '18 at 7:32
Dave
434
asked Nov 14 '18 at 1:17
HelloWorldHelloWorld
4418
add a comment |
I have JSON data structured like this:
[
"eventName": "unmuteClick",
"intPayload":0,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099009,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "muteClick",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099009,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "resumeClick",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 15416320990586,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "pauseClick",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 15416320990585,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "mediaDuration",
"intPayload":10000,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "firstQuartileCount",
"intPayload": 1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "secondQuartileCount",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "thirdQuartileCount",
"intPayload":0,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "completeCount",
"intPayload":0,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v"
]
Each record is a different event that can happen during video playback. One video playback has a unique playbackId, so you can see there are 10 events related to the same playback.
What I need to do is aggregate and transform this data to CSV format, where each row would be aggregated results for one playbackId.
I need to transform the values in the eventName field into columns, where the values in the intPayload field are the values of the columns.
Here is the schema I need to use:
playbackId, sessionId, pageAsin, videoAsin, unmuteClick,muteClick, pauseClick, resumeClick, mediaDuration,firstQuartileCount, secondQuartileCount,thirdQuartileCount,completeCount
Based on the data, values for the schema would be like this:
"49309k-54353esfs-resf43-23fs43jk","324435-65657-3256-8787", "B00K7GXXKQ", "B078LXG579v",1,1,1,1,10000,1,1,0,0"
(For the same playbackId, fields like sessionId, pageAsin and videoAsin would be the same.)
Does anything already exist for transformations and aggregations like this? Can I use Elastic Map reduce for calculations like this? The input data size is pretty large.
json amazon-web-services mapreduce aggregate amazon-emr
edited Nov 14 '18 at 7:32
Dave
434
asked Nov 14 '18 at 1:17
HelloWorldHelloWorld
4418
add a comment |
I have JSON data structured like this:
[
"eventName": "unmuteClick",
"intPayload":0,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099009,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "muteClick",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099009,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "resumeClick",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 15416320990586,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "pauseClick",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 15416320990585,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "mediaDuration",
"intPayload":10000,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "firstQuartileCount",
"intPayload": 1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "secondQuartileCount",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "thirdQuartileCount",
"intPayload":0,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "completeCount",
"intPayload":0,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v"
]
Each record is a different event that can happen during video playback. One video playback has a unique playbackId, so you can see there are 10 events related to the same playback.
What I need to do is aggregate and transform this data to CSV format, where each row would be aggregated results for one playbackId.
I need to transform the values in the eventName field into columns, where the values in the intPayload field are the values of the columns.
Here is the schema I need to use:
playbackId, sessionId, pageAsin, videoAsin, unmuteClick,muteClick, pauseClick, resumeClick, mediaDuration,firstQuartileCount, secondQuartileCount,thirdQuartileCount,completeCount
Based on the data, values for the schema would be like this:
"49309k-54353esfs-resf43-23fs43jk","324435-65657-3256-8787", "B00K7GXXKQ", "B078LXG579v",1,1,1,1,10000,1,1,0,0"
(For the same playbackId, fields like sessionId, pageAsin and videoAsin would be the same.)
Does anything already exist for transformations and aggregations like this? Can I use Elastic Map reduce for calculations like this? The input data size is pretty large.
json amazon-web-services mapreduce aggregate amazon-emr
edited Nov 14 '18 at 7:32
Dave
434
asked Nov 14 '18 at 1:17
HelloWorldHelloWorld
4418
I have JSON data structured like this:
[
"eventName": "unmuteClick",
"intPayload":0,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099009,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "muteClick",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099009,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "resumeClick",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 15416320990586,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "pauseClick",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 15416320990585,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "mediaDuration",
"intPayload":10000,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "firstQuartileCount",
"intPayload": 1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "secondQuartileCount",
"intPayload":1,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "thirdQuartileCount",
"intPayload":0,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v",
"eventName": "completeCount",
"intPayload":0,
"stringPayload": "",
"playbackId": "49309k-54353esfs-resf43-23fs43jk",
"sessionId": "324435-65657-3256-8787",
"timestamp": 1541632099010,
"pageAsin": "B00K7GXXKQ",
"videoAsin": "B078LXG579v"
]
Each record is a different event that can happen during video playback. One video playback has a unique playbackId, so you can see there are 10 events related to the same playback.
What I need to do is aggregate and transform this data to CSV format, where each row would be aggregated results for one playbackId.
I need to transform the values in the eventName field into columns, where the values in the intPayload field are the values of the columns.
Here is the schema I need to use:
playbackId, sessionId, pageAsin, videoAsin, unmuteClick,muteClick, pauseClick, resumeClick, mediaDuration,firstQuartileCount, secondQuartileCount,thirdQuartileCount,completeCount
Based on the data, values for the schema would be like this:
"49309k-54353esfs-resf43-23fs43jk","324435-65657-3256-8787", "B00K7GXXKQ", "B078LXG579v",1,1,1,1,10000,1,1,0,0"
(For the same playbackId, fields like sessionId, pageAsin and videoAsin would be the same.)
Does anything already exist for transformations and aggregations like this? Can I use Elastic Map reduce for calculations like this? The input data size is pretty large.
json amazon-web-services mapreduce aggregate amazon-emr
json amazon-web-services mapreduce aggregate amazon-emr
edited Nov 14 '18 at 7:32
Dave
434
asked Nov 14 '18 at 1:17
HelloWorldHelloWorld
4418
edited Nov 14 '18 at 7:32
Dave
434
asked Nov 14 '18 at 1:17
HelloWorldHelloWorld
4418
edited Nov 14 '18 at 7:32
Dave
434
edited Nov 14 '18 at 7:32
Dave
434
edited Nov 14 '18 at 7:32
Dave
434
434
asked Nov 14 '18 at 1:17
HelloWorldHelloWorld
4418
asked Nov 14 '18 at 1:17
HelloWorldHelloWorld
4418
asked Nov 14 '18 at 1:17
HelloWorldHelloWorld
4418
4418
add a comment |
add a comment |
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