Elasticsearch API
Basics
  1. # Syntax
  2. # GET _API/parameter
  3.  
  4. # Cluster health
  5. GET _cluster/health
  6.  
  7. # Node info
  8. GET _nodes/stats
  9.  
  10. # Get index info
  11. # GET index_name
  12. GET c_house_price
  13.  
  14. # List indices
  15. GET /_cat/indices
  16.
Create, Read, Update, and Delete (CRUD)
  • Create index
    1. # PUT index_name
    2. PUT c_house_price
    3.  
    4. # Create index with mapping
    5. PUT ecommerce_data
    6. {
    7.   "mappings": {
    8.     "properties": {
    9.       "Country": {
    10.         "type": "keyword"
    11.       },
    12.       "CustomerID": {
    13.         "type": "long"
    14.       },
    15.       "Description": {
    16.         "type": "text"
    17.       },
    18.       "InvoiceDate": {
    19.         "type": "date",
    20.         "format": "M/d/yyyy H:m"
    21.       },
    22.       "InvoiceNo": {
    23.         "type": "keyword"
    24.       },
    25.       "Quantity": {
    26.         "type": "long"
    27.       },
    28.       "StockCode": {
    29.         "type": "keyword"
    30.       },
    31.       "UnitPrice": {
    32.         "type": "double"
    33.       }
    34.     }
    35.   }
    36. }
    37.
  • Insert document
    1. # POST index_name/_doc
    2. # PUT does not work
    3. POST c_house_price/_doc
    4. {
    5.   "first_name": "Lin",
    6.   "last_name": "Chen"
    7. }
    8.  
    9. # Insert a document with a specific id
    10. # PUT index_name/_doc/id
    11. # POST index_name/_doc/id
    12. # if id already exists, the existing document is overwritten by the new document
    13. PUT c_house_price/_doc/1
    14. {
    15.   "first_name": "John",
    16.   "last_name": "Starburst"
    17. }
    18.  
    19. # if id already exist, return 409 error
    20. # PUT index_name/_create/id
    21. # POST index_name/_create/id
    22. PUT c_house_price/_create/3
    23. {
    24.   "first_name": "Lin",
    25.   "candy": "Jolly Ranchers"
    26. }
    27.  
    28. # reindex to create an index from an original index
    29. # run the task asynchronously to avoid timeout
    30. POST _reindex?wait_for_completion=false
    31. {
    32.   "source": {
    33.     "index": "e_commerce"
    34.   },
    35.   "dest": {
    36.     "index": "ecommerce_data"
    37.   }
    38. }
    39.  
    40. # use task id to check the progress
    41. GET _tasks/task_id
    42.
  • Read a document
    1. # GET index_name/_doc/id
    2. GET c_house_price/_doc/1
    3.
  • Update a document
    1. # POST index_name/_update/id
    2. POST c_house_price/_update/1
    3. {
    4.   "doc":{
    5.     "last_name": "Chen"
    6.   }
    7. }
    8.
  • Delete a document
    1. # DELETE index_name/_doc/id
    2. DELETE c_house_price/_doc/1
    3.  
    4. # Delete an index
    5. # DELETE index_name
    6. DELETE c_house_price
    7.  
    8. # Delete by query
    9. POST ecommerce_data/_delete_by_query
    10. {
    11.   "query": {
    12.     "range": {
    13.       "UnitPrice": {
    14.         "lte": 0
    15.       }
    16.     }
    17.   }
    18. }
    19.
    Bulk
  • Insert
    1. POST _bulk
    2. {"index": {"_index": "baseline_1", "_id":1}}
    3. {"Absolute vorticity": 0.0001307,"Apparent temperature": 232.5}
    4. {"index": {"_index": "baseline_1", "_id":2}}
    5. {"Absolute vorticity": 0.0001307,"Apparent temperature": 233.6} 
    6.
  • Update
    1. POST _bulk
    2. {"update": {"_index": "baseline_1", "_id": 1}}
    3. {"doc": {"Apparent temperature": 242.5}}
    4. {"update": {"_index": "baseline_1", "_id":2}}
    5. {"doc": {"Apparent temperature": 243.6}}
    6.
  • Delete
    1. POST _bulk
    2. {"delete": {"_index": "baseline_1", "_id": 1}}
    3. {"delete": {"_index": "baseline_1", "_id":2}}
    4.
    Query
  • Query Types 
    1. # Search
    2. # GET index_name/_search
    3. GET news_headlines/_search # return 10,000 hits
    4. # GET index_pattern/_search
    5. GET c*/_search
    6.  
    7. # return exact total number of hits
    8. GET news_headlines/_search
    9. {
    10.   "track_total_hits": true 
    11. }
    12.
  • match all query
    1. POST news_headlines/_search
    2. {
    3.    "query":{
    4.       "match_all":{}
    5.    }
    6. }
    7.
  • Search between two date
    1. GET enter_name_of_the_index_here/_search
    2. {
    3.   "query": {
    4.     "Specify the type of query here": {
    5.       "Enter name of the field here": {
    6.         "gte": "Enter lowest value of the range here",
    7.         "lte": "Enter highest value of the range here"
    8.       }
    9.     }
    10.   }
    11. }
    12.             
    1. GET news_headlines/_search
    2. {
    3.   "query":{
    4.       "range": {
    5.         "date": {
    6.           "gte": "2017-05-28T00:00:00.000-04:00",
    7.           "lt": "2017-12-26T00:00:00.000-05:00"
    8.         }
    9.       }
    10.     }
    11. }
    12.
  • Match Query 
    1. GET Enter_name_of_index_here/_search
    2. {
    3.   "query": {
    4.     "match": {
    5.       "Specify the field you want to search": {
    6.         "query": "Enter search terms"
    7.       }
    8.     }
    9.   }
    10. }
    11.             
    1. # all, if any one of the term match, return as a hit
    2. GET news_headlines/_search
    3. {
    4.   "query": {
    5.     "match": {
    6.       "headline": {
    7.         "query": "Khloe Kardashian Kendall Jenner" # search keywords in headline
    8.       }
    9.     }
    10.   }
    11. }
    12.  
    13. # and, all terms need to match
    14. GET news_headlines/_search
    15. {
    16.   "query": {
    17.     "match": {
    18.       "headline": {
    19.         "query": "Khloe Kardashian Kendall Jenner",
    20.         "operator": "and"
    21.       }
    22.     
    23.   }
    24. }
    25.  
    26. # specify the minimum number of terms a document should have to be included
    27. GET news_headlines/_search
    28. {
    29.   "query": {
    30.     "match": {
    31.       "headline": {
    32.         "query": "Khloe Kardashian Kendall Jenner",
    33.         "minimum_should_match": 3
    34.       }
    35.     }
    36.   }
    37. }
    38.
  • Match_phase Query 
    1. GET Enter_name_of_index_here/_search
    2. {
    3.   "query": {
    4.     "match_phrase": {
    5.       "Specify the field you want to search": {
    6.         "query": "Enter search terms"
    7.       }
    8.     }
    9.   }
    10. }
    11.             
    1. GET news_headlines/_search
    2. {
    3.   "query": {
    4.     "match_phrase": {
    5.       "headline": {
    6.         "query": "Shape of You"
    7.       }
    8.     }
    9.   }
    10. }
    11.
  • Query Multiple Fields
    1. GET Enter_the_name_of_the_index_here/_search
    2. {
    3.   "query": {
    4.     "multi_match": {
    5.       "query": "Enter search terms here",
    6.       "fields": [
    7.         "List the field you want to search over",
    8.         "List the field you want to search over",
    9.         "List the field you want to search over"
    10.       ]
    11.     }
    12.   }
    13. }
    14.             
    1. GET news_headlines/_search
    2. {
    3.   "query": {
    4.     "multi_match": {
    5.       "query": "Michelle Obama",
    6.       "fields": [
    7.         "headline",
    8.         "short_description",
    9.         "authors"
    10.       ]
    11.     }
    12.   }
    13. }
    14.             
    1. # designate one field to carry more weight than the others
    2. # by ^number
    3. GET Enter_the_name_of_the_index_here/_search
    4. {
    5.   "query": {
    6.     "multi_match": {
    7.       "query": "Enter search terms",
    8.       "fields": [
    9.         "List field you want to boost^2",
    10.         "List field you want to search over",
    11.         "List field you want to search over^3"
    12.       ]
    13.     }
    14.   }
    15. }
    16.             
    1. GET news_headlines/_search
    2. {
    3.   "query": {
    4.     "multi_match": {
    5.       "query": "Michelle Obama",
    6.       "fields": [
    7.         "headline^2",
    8.         "short_description",
    9.         "authors"
    10.       ]
    11.     }
    12.   }
    13. }
    14.             
    1. # improve precision with phrase type match
    2. GET Enter_the_name_of_the_index_here/_search
    3. {
    4.   "query": {
    5.     "multi_match": {
    6.       "query": "Enter search phrase",
    7.       "fields": [
    8.         "List field you want to boost^2",
    9.         "List field you want to search over",
    10.         "List field you want to search over"
    11.       ],
    12.       "type": "phrase"
    13.     }
    14.   }
    15. }
    16.             
    1. GET news_headlines/_search
    2. {
    3.   "query": {
    4.     "multi_match": {
    5.       "query": "party planning",
    6.       "fields": [
    7.         "headline^2",
    8.         "short_description"
    9.       ],
    10.       "type": "phrase"
    11.     }
    12.   }
    13. }
    14.
  • Combine multiple queries
    1. GET index_name/_search
    2. {
    3.     "query":{
    4.         "bool":{
    5.             "must":[{}], # items must appear in matching documents, AND
    6.             "must_not":[{}], # NOT
    7.             "should":[{}], # at least one of items appear in matching documents, OR
    8.             "filter":[{}] # query filter
    9.         }
    10.     }
    11. }
    12.  
    13. # must
    14. GET news_headlines/_search
    15. {
    16.   "query": {
    17.     "bool": {
    18.       "must": [
    19.         {
    20.         "match_phrase": {
    21.           "headline": "Michelle Obama"
    22.          }
    23.         },
    24.         {
    25.           "match": {
    26.             "category": "POLITICS"
    27.           }
    28.         }
    29.       ]
    30.     }
    31.   }
    32. }
    33.  
    34. # must_not
    35. GET news_headlines/_search
    36. {
    37.   "query": {
    38.     "bool": {
    39.       "must": {
    40.         "match_phrase": {
    41.           "headline": "Michelle Obama"
    42.          }
    43.         },
    44.        "must_not":[
    45.          {
    46.           "match": {
    47.             "category": "WEDDINGS"
    48.           }
    49.         }
    50.       ]
    51.     }
    52.   }
    53. }
    54.  
    55. # should
    56. GET news_headlines/_search
    57. {
    58.   "query": {
    59.     "bool": {
    60.       "must": [
    61.         {
    62.         "match_phrase": {
    63.           "headline": "Michelle Obama"
    64.           }
    65.          }
    66.         ],
    67.        "should":[
    68.          {
    69.           "match_phrase": {
    70.             "category": "BLACK VOICES"
    71.           }
    72.         }
    73.       ]
    74.     }
    75.   }
    76. }
    77.  
    78. # filter
    79. GET news_headlines/_search
    80. {
    81.   "query": {
    82.     "bool": {
    83.       "must": [
    84.         {
    85.         "match_phrase": {
    86.           "headline": "Michelle Obama"
    87.           }
    88.          }
    89.         ],
    90.        "filter":{
    91.           "range":{
    92.              "date": {
    93.                "gte": "2014-03-25",
    94.                "lte": "2016-03-25"
    95.           }
    96.         }
    97.       }
    98.     }
    99.   }
    100. }
    101.  
    102. GET news_headlines/_search
    103. {
    104.   "query": {
    105.     "bool": {
    106.       "should": [
    107.         {
    108.           "match_phrase": {
    109.             "category": "ENTERTAINMENT"
    110.           }
    111.         }
    112.       ],
    113.       "filter": [
    114.       {
    115.         "exists": {
    116.           "field": "headline"
    117.         }
    118.       }
    119.       ]
    120.     }
    121.   }
    122. }
    123.
  • Geo queries
    1. POST /geo_example/_doc?refresh
    2. {
    3.     "name": "Chapter One, London, UK",
    4.     "location": {
    5.         "type": "point",
    6.         "coordinates": [11.660544, 57.800286]
    7.     }
    8. }
    9.
    Aggregation
  • Metric Aggregations
  • Bucket Aggregations 
    1. GET Enter_name_of_the_index_here/_search
    2. {
    3.   "aggs": {
    4.     "Name your aggregation here": {
    5.       "Specify aggregation type here": { # terms, stats, geodistance
    6.         "field": "Name the field you want to aggregate here",
    7.         "size": "State how many buckets you want returned here"
    8.       }
    9.     }
    10.   }
    11. }
    12.             
    1. GET news_headlines/_search
    2. {
    3.   "aggs": {
    4.     "by_category": { # aggregation name
    5.       "terms": { # aggregation type
    6.         "field": "category", # filed name
    7.         "size": 100 # number of buckets returns
    8.       }
    9.     }
    10.   }
    11. }
    12.
  • Metric Aggregations
    1. GET Enter_name_of_the_index_here/_search
    2. {
    3.   "aggs": {
    4.     "Name your aggregations here": {
    5.       "sum": {
    6.         "field": "Name the field you want to aggregate on here"
    7.       }
    8.     }
    9.   }
    10. }
    11.             
    1. # sum
    2. GET ecommerce_data/_search
    3. {
    4.   "size": 0, # prevents Elasticsearch from fetching the top 10 hits
    5.   "aggs": {
    6.     "sum_unit_price": {
    7.       "sum": {
    8.         "field": "UnitPrice"
    9.       }
    10.     }
    11.   }
    12. }
    13.             
    1. # stats, list count, min, max, avg, sum
    2. GET ecommerce_data/_search
    3. {
    4.   "size": 0,
    5.   "aggs": {
    6.     "all_stats_unit_price": {
    7.       "stats": {
    8.         "field": "UnitPrice"
    9.       }
    10.     }
    11.   }
    12. }
    13.             
    1. # Cardinality Aggregation
    2. GET ecommerce_data/_search
    3. {
    4.   "size":0,
    5.   "aggs": {
    6.     "sum_unit_price": {
    7.       "cardinality": {
    8.         "field": "CustomerID"
    9.       }
    10.     }
    11.   }
    12. }
    13.             
    1. # Limiting the scope of an aggregation
    2. GET ecommerce_data/_search
    3. {
    4.   "size": 0,
    5.   "query": {
    6.     "match": {
    7.       "Country": "Germany"
    8.     }
    9.   },
    10.   "aggs": {
    11.     "germany_average_unit_price": {
    12.       "avg": {
    13.         "field": "UnitPrice"
    14.       }
    15.     }
    16.   }
    17. }
    18.
  • Bucket Aggregations
    1. # Date Histogram Aggregation
    2. GET ecommerce_data/_search
    3. {
    4.   "size": 0,
    5.   "aggs": {
    6.     "Name your aggregations here": {
    7.       "date_histogram": {
    8.         "field":"Name the field you want to aggregate on here",
    9.         "fixed_interval": "Specify the interval here"
    10.       }
    11.     }
    12.   }
    13. }
    14.  
    15. GET ecommerce_data/_search
    16. {
    17.   "size": 0,
    18.   "aggs": {
    19.     "transactions_by_8_hrs": {
    20.       "date_histogram": {
    21.         "field": "InvoiceDate",
    22.         "fixed_interval": "8h"
    23.       }
    24.     }
    25.   }
    26. }
    27.  
    28. GET ecommerce_data/_search
    29. {
    30.   "size": 0,
    31.   "aggs": {
    32.     "Name your aggregations here": {
    33.       "date_histogram": {
    34.         "field":"Name the field you want to aggregate on here",
    35.         "calendar_interval": "Specify the interval here"
    36.       }
    37.     }
    38.   }
    39. }
    40.  
    41. GET ecommerce_data/_search
    42. {
    43.   "size": 0,
    44.   "aggs": {
    45.     "transactions_by_month": {
    46.       "date_histogram": {
    47.         "field": "InvoiceDate",
    48.         "calendar_interval": "1M"
    49.         "order": {
    50.           "_key": "desc"
    51.         }
    52.       }
    53.     }
    54.   }
    55. }
    56.             
    1. # Histogram Aggregation
    2. GET ecommerce_data/_search
    3. {
    4.   "size": 0,
    5.   "aggs": {
    6.     "Name your aggregations here": {
    7.       "histogram": {
    8.         "field":"Name the field you want to aggregate on here",
    9.         "interval": Specify the interval here
    10.       }
    11.     }
    12.   }
    13. }
    14.  
    15. GET ecommerce_data/_search
    16. {
    17.   "size": 0,
    18.   "aggs": {
    19.     "transactions_per_price_interval": {
    20.       "histogram": {
    21.         "field": "UnitPrice",
    22.         "interval": 10
    23.       }
    24.     }
    25.   }
    26. }
    27.             
    1. # Range Aggregation
    2. GET Enter_name_of_the_index_here/_search
    3. {
    4.   "size": 0,
    5.   "aggs": {
    6.    "Name your aggregations here": {
    7.       "range": {
    8.         "field": "Name the field you want to aggregate on here",
    9.         "ranges": [
    10.           {
    11.             "to": x
    12.           },
    13.           {
    14.             "from": x,
    15.             "to": y
    16.           },
    17.           {
    18.             "from": z
    19.           }
    20.         ]
    21.       }
    22.     }
    23.   }
    24. }
    25.  
    26. GET ecommerce_data/_search
    27. {
    28.   "size": 0,
    29.   "aggs": {
    30.     "transactions_per_custom_price_ranges": {
    31.       "range": {
    32.         "field": "UnitPrice",
    33.         "ranges": [
    34.           {
    35.             "to": 50
    36.           },
    37.           {
    38.             "from": 50,
    39.             "to": 200
    40.           },
    41.           {
    42.             "from": 200
    43.           }
    44.         ]
    45.       }
    46.     }
    47.   }
    48. }
    49.             
    1. # Terms Aggregation
    2. GET Enter_name_of_the_index_here/_search
    3. {
    4.   "aggs": {
    5.     "Name your aggregations here": {
    6.       "terms": {
    7.         "field": "Name the field you want to aggregate on here",
    8.         "size": State how many top results you want returned here
    9.       }
    10.     }
    11.   }
    12. }
    13.  
    14. GET ecommerce_data/_search
    15. {
    16.   "size": 0,
    17.   "aggs": {
    18.     "top_5_customers": {
    19.       "terms": {
    20.         "field": "CustomerID",
    21.         "size": 5
    22.       }
    23.     }
    24.   }
    25. }
    26.
  • Combined Aggregations
    1. GET ecommerce_data/_search
    2. {
    3.   "size": 0,
    4.   "aggs": {
    5.     "transactions_per_day": {
    6.       "date_histogram": {
    7.         "field": "InvoiceDate",
    8.         "calendar_interval": "day"
    9.       },
    10.       "aggs": {
    11.         "daily_revenue": {
    12.           "sum": {
    13.             "script": {
    14.               "source": "doc['UnitPrice'].value * doc['Quantity'].value"
    15.             }
    16.           }
    17.         }
    18.       }
    19.     }
    20.   }
    21. }
    22.  
    23. GET ecommerce_data/_search
    24. {
    25.   "size": 0,
    26.   "aggs": {
    27.     "transactions_per_day": {
    28.       "date_histogram": {
    29.         "field": "InvoiceDate",
    30.         "calendar_interval": "day"
    31.       },
    32.       "aggs": {
    33.         "daily_revenue": {
    34.           "sum": {
    35.             "script": {
    36.               "source": "doc['UnitPrice'].value * doc['Quantity'].value"
    37.             }
    38.           }
    39.         },
    40.         "number_of_unique_customers_per_day": {
    41.           "cardinality": {
    42.             "field": "CustomerID"
    43.           }
    44.         }
    45.       }
    46.     }
    47.   }
    48. }
    49.
    Query and Aggregation
  • Pull documents with query, then analyze the query data and create summary with aggregations
    1. GET Enter_name_of_the_index_here/_search
    2. {
    3.   "query": {
    4.     "Enter match or match_phrase here": { "Enter the name of the field": "Enter the value you are looking for" }
    5.   },
    6.   "aggs": {
    7.     "Name your aggregation here": {
    8.       "Specify aggregation type here": {
    9.         "field": "Name the field you want to aggregate here",
    10.         "size": "State how many buckets you want returned here"
    11.       }
    12.     }
    13.   }
    14. }
    15.             
    1. GET news_headlines/_search
    2. {
    3.   "query": {
    4.     "match": {
    5.       "category": "ENTERTAINMENT"
    6.     }
    7.   },
    8.   "aggs": {
    9.     "popular_in_entertainment": { # aggregation name
    10.       "significant_text": { # aggregation type
    11.         "field": "headline"
    12.       }
    13.     }
    14.   }
    15. }
    16.
    Mapping
  • defines how a document and its fields are indexed and stored
  • help optimize the performance of Elasticsearch and save disk space
  • Rules
  • String types
  • View Mapping
    1. GET Enter_name_of_the_index_here/_mapping
    2.  
    3. GET temp_index/_mapping
    4.
  • Create an index with Mapping
    1. PUT produce_index
    2. {
    3.   "mappings": {
    4.     "properties": {
    5.       "botanical_name": {
    6.         "enabled": false # disabled to save disk space
    7.       },
    8.       "country_of_origin": { # text and keyword
    9.         "type": "text",
    10.         "fields": {
    11.           "keyword": {
    12.             "type": "keyword"
    13.           }
    14.         }
    15.       },
    16.       "date_purchased": { # date
    17.         "type": "date"
    18.       },
    19.       "description": { # text
    20.         "type": "text"
    21.       },
    22.       "name": { # text
    23.         "type": "text"
    24.       },
    25.       "produce_type": { # keyword
    26.         "type": "keyword"
    27.       },
    28.       "quantity": {
    29.         "type": "long"
    30.       },
    31.       "unit_price": {
    32.         "type": "float"
    33.       },
    34.       "vendor_details": {
    35.         "enabled": false
    36.       }
    37.     }
    38.   }
    39. }
    40.
  • Update Mapping
    1. # step 1, create a new index
    2. PUT produce_v2
    3. {
    4.   "mappings": {
    5.     "properties": {
    6.       "botanical_name": {
    7.         "type": "text"
    8.       },
    9.       "country_of_origin": {
    10.         "type": "text",
    11.         "fields": {
    12.           "keyword": {
    13.             "type": "keyword",
    14.             "ignore_above": 256
    15.           }
    16.         }
    17.       },
    18.       "date_purchased": {
    19.         "type": "date"
    20.       },
    21.       "description": {
    22.         "type": "text"
    23.       },
    24.       "name": {
    25.         "type": "text"
    26.       },
    27.       "organic": {
    28.         "type": "boolean"
    29.       },
    30.       "produce_type": {
    31.         "type": "keyword"
    32.       },
    33.       "quantity": {
    34.         "type": "long"
    35.       },
    36.       "unit_price": {
    37.         "type": "float"
    38.       },
    39.       "vendor_details": {
    40.         "type": "object",
    41.         "enabled": false
    42.       }
    43.     }
    44.   }
    45. }
    46.             
    1. # step 2: Reindex the data from the original index(produce_index) to the one you just created(produce_v2)
    2. # reindex copys existing data from a source index to a destination index
    3. POST _reindex
    4. {
    5.   "source": {
    6.     "index": "produce_index"
    7.   },
    8.   "dest": {
    9.     "index": "produce_v2"
    10.   }
    11. }
    12.
    Runtime Field
  • Enable to create and query fields that are evaluated only at query time
  • Runtime fields are not physically saved in the index
    1. # step 1. create a runtime field and add it to the mapping of the existing index
    2. PUT Enter-name-of-index/_mapping
    3. {
    4.   "runtime": {
    5.     "Name-your-runtime-field-here": {
    6.       "type": "Specify-field-type-here",
    7.       "script": {
    8.         "source": "Specify the formula you want executed"
    9.       }
    10.     }
    11.   }
    12. }
    13.             
    1. PUT produce_v2/_mapping
    2. {
    3.   "runtime": {
    4.     "total": {
    5.       "type": "double",
    6.       "script": {
    7.         "source": "emit(doc['unit_price'].value* doc['quantity'].value)"
    8.       }
    9.     }
    10.   }
    11. }
    12.             
    1. # step 2. use runtime fields
    2. GET Enter_name_of_the_index_here/_search
    3. {
    4.   "size": 0,
    5.   "aggs": {
    6.     "Name your aggregations here": {
    7.       "Specify the aggregation type here": {
    8.         "field": "Name the field you want to aggregate on here"
    9.       }
    10.     }
    11.   }
    12. }
    13.             
    1. GET produce_v2/_search
    2. {
    3.   "size": 0,
    4.   "aggs": {
    5.     "total_expense": {
    6.       "sum": {
    7.         "field": "total"
    8.       }
    9.     }
    10.   }
    11. }
    12.
    Troubleshooting
  • 5XX errors
  • 4XX errors
    • Reference
  • Field data types
  • Tutorialspoint
  • REST APIs
  • Beginner's Crash Course to Elastic Stack at Yourtube
  • Cheatsheet
  • Beginner's Crash Course to Elastic Stack Series at Github
  • Getting Started with Kibana (tutorial) at Youtube