stelcheck/hbase.rest.scanner.filters.md

## hbase.rest.scanner.filters.md

      
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              hbase.rest.scanner.filters.md
            
          
    Stargate Scanner Filter Examples

Introduction

So yeah... no documentation for the HBase REST API in regards to what should a filter look like...
So I installed Eclipse, got the library, and took some time to find some of the (seemingly) most useful filters you could use. I'm very green at anything regarding HBase, and I hope this will help anyone trying to get started with it.
What I discovered is that basically, attributes of the filter object follow the same naming than in the documentation. For this reason, I have made the link clickable and direct them to the HBase Class documentation attached to it; check for the instantiation argument names, and you will have your attribute list (more or less).
Don't forget, values are encoded.
References:


HBase REST Filter (SingleColumnValueFilter)
HBase Intra-row scanning
HBase Book / Chapter on Client Filter

ColumnPrefixFilter

{
  "type": "ColumnPrefixFilter",
  "value": "cHJlZml4"
}
ColumnRangeFilter

{
  "type": "ColumnRangeFilter",
  "minColumn": "Zmx1ZmZ5",
  "minColumnInclusive": true,
  "maxColumn": "Zmx1ZmZ6",
  "maxColumnInclusive": false
}
ColumnPaginationFilter

Could not generate an example, but I guess it should be pretty simple to test if it works just by intuitively plugging variables a certain way...
DependentColumnFilter

null
FamilyFilter

{
  "type": "FamilyFilter",
  "op": "EQUAL",
  "comparator": {
    "type": "BinaryComparator",
    "value": "dGVzdHJvdw\u003d\u003d"
  }
}
FilterList with RowFilter and ColumnRangeFilter

{
  "type": "FilterList",
  "op": "MUST_PASS_ALL",
  "filters": [
    {
      "type": "RowFilter",
      "op": "EQUAL",
      "comparator": {
        "type": "BinaryComparator",
        "value": "dGVzdHJvdw\u003d\u003d"
      }
    },
    {
      "type": "ColumnRangeFilter",
      "minColumn": "Zmx1ZmZ5",
      "minColumnInclusive": true,
      "maxColumn": "Zmx1ZmZ6",
      "maxColumnInclusive": false
    }
  ]
}
FirstKeyOnlyFilter (Can be used for more efficiently perform row count operation)

{
  "type": "FirstKeyOnlyFilter"
}
InclusiveStopFilter

{
  "type": "InclusiveStopFilter",
  "value": "cm93a2V5"
}
MultipleColumnPrefixFilter

{
  "type": "MultipleColumnPrefixFilter",
  "prefixes": [
    "YWxwaGE\u003d",
    "YnJhdm8\u003d",
    "Y2hhcmxpZQ\u003d\u003d"
  ]
}
PageFilter

{
  "type": "PageFilter",
  "value": "10"
}
PrefixFilter

{
  "type": "PrefixFilter",
  "value": "cm93cHJlZml4"
}
QualifierFilter

{
  "type": "QualifierFilter",
  "op": "GREATER",
  "comparator": {
    "type": "BinaryComparator",
    "value": "cXVhbGlmaWVycHJlZml4"
  }
}
RowFilter

{
  "type": "RowFilter",
  "op": "EQUAL",
  "comparator": {
    "type": "BinaryComparator",
    "value": "dGVzdHJvdw\u003d\u003d"
  }
}
SingleColumnValueFilter

{
  "type": "SingleColumnValueFilter",
  "op": "EQUAL",
  "family": "ZmFtaWx5",
  "qualifier": "Y29sMQ\u003d\u003d",
  "latestVersion": true,
  "comparator": {
    "type": "BinaryComparator",
    "value": "MQ\u003d\u003d"
  }
}
TimestampsFilter

{
  "type": "TimestampsFilter",
  "timestamps": [
    "1351586939"
  ]
}